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Journal of Medicine and Pharmacy","Tạp chí Y Dược học Cần Thơ",{"EN":487,"VI":488},"\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">04\u002F10\u002F2015 Ministry of Information and Communications allowed Can Tho journal of medicine and pharmacy to operate (102 \u002FGP-BTTTT)\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">07\u002F16\u002F2015 Can Tho journal of medicine and pharmacy is internationally recognized: ISSN 2354-1210\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">In 2016, The journal has been included in the list of medical science journals by The State Council for professorship which is awarded a work score of 0-0.5 points for a published article.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Can Tho Journal of Medicine and Pharmacy welcome original works that haven’t been submitted or published in other medical journals. Posts must contain content related to one of the journal’s categories.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">The content published\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">The journal is divided into 3 categories:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Scientific research article: are valuable scientific works, which have been researched and accepted.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Overview of medicine, biology and pharmacy: serving the objective of continuing training in the fields of medicine, biology and pharmacy; to systematize classical and modern knowledge.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Update information on new knowledge about medicine, biology, pharmacy in the country and in the world.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Scope\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Publication and introduction of scientific research in the fields:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">+ Medicine (internal medicine, surgery, pediatrics, obstetrics and gynecology, odonto-stomatology, laboratory, oncology, traditional medicine, nursing).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">+ Biology (genetics, biotechnology).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">+ Pharmacology (pharmaceutics, drug quality analysis-control, synthetic pharmaceutical chemistry, biochemistry, pharmacognosy, botany, clinical pharmacy).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- To enhance the quality of undergraduate, postgraduate education, scientifically researching and meet the necessary treatment in hospital.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Introducing the updated domestic and oversea information about science technology to promote scientific research and exchanging technology in local, other universities.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">- Exchanging pharmaceutical and medical information for social health developing in the Mekong Delta and Vietnam.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">The object\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Postgraduate students, student of Can Tho University of Medicine and Pharmacy, scientists from schools, research institutes, hospitals, health centers, pharmaceutical companies of the Mekong Delta; other provinces and regions in Vietnam and other country.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Address\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Headquarters of Can Tho Journal of Medicine and Pharmacy, located Scientific Research and International Cooperation Office: 179 Nguyen Van Cu Street, An Khanh Ward, Ninh Kieu District, Can Tho City, Vietnam.\u003C\u002Fspan>\u003C\u002Fp>","\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Ngày 16\u002F7\u002F2015, Tạp chí Y Dược học Cần Thơ được cấp chỉ số quốc tế: ISSN 2354-1210.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Từ tháng 4\u002F2016, Tạp chí đã được Hội đồng Giáo sư ngành Y đưa vào danh sách các tạp chí khoa học Y học được tính điểm công trình 0-0,5 điểm cho một bài báo đăng.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Năm 2020 Tạp chí Y Dược học Cần Thơ đã được phê duyệt vào danh mục của các Hội đồng Giáo sư ngành Dược học được tính điểm công trình 0-0,5 điểm cho một bài báo đăng.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ ra 12 số\u002Fnăm, 180-200 trang\u002Fsố.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Từ tháng 12\u002F2022 Tạp chí Y Dược học Cần Thơ là thành viên của hệ thống Crossref và từ tháng 01\u002F2023 tạp chí thực hiện bình duyệt online kín 2 chiều nhằm tăng tính minh bạch, tin cậy của các công trình nghiên cứu khoa học và đảm bảo tốt nhất chất lượng khoa học của bài viết.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tôn chỉ, mục đích và phạm vi của tạp chí\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tôn chỉ và mục đích hoạt động của tạp chí: xuất bản nhằm mục đích phổ biến kết quả từ các đề tài nghiên cứu khoa học; giao lưu trao đổi khoa học, chia sẻ kinh nghiệm, học tập, đồng thời cập nhật thông tin khoa học mới trong các lĩnh vực y, sinh, dược học trong và ngoài nước.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Phạm vi của tạp chí: Tạp chí xuất bản được chia thành 3 chuyên mục: (i) Bài báo nghiên cứu khoa học là kết quả công trình nghiên cứu khoa học có giá trị đã được triển khai nghiên cứu, (ii) Bài tổng quan y, sinh, dược học: phục vụ mục tiêu đào tạo liên tục trong lĩnh vực y, sinh, dược học; nhằm hệ thống hóa những kiến thức kinh điển và hiện đại; (iii) Thông tin cập nhật kiến thức mới về y, sinh, dược học trong nước và trên thế giới.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Chính sách truy cập mở\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ áp dụng chính sách truy cập mở đối với các bài báo đã xuất bản đến với độc giả, nhằm mở rộng cơ hội tiếp cận các kết quả nghiên cứu chất lượng cao và tăng cường trao đổi kiến thức. Tạp chí đăng tải trực tuyến (miễn phí) toàn văn các bài báo được công bố trên website của Tạp chí (https:\u002F\u002Ftapchi.ctump.edu.vn).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Đạo đức xuất bản\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ cam kết tuân thủ đạo đức xuất bản phù hợp với các hướng dẫn và tiêu chuẩn của the Committee on Publication Ethics (COPE), tuân thủ các nguyên tắc của COPE’s Core Practices, Best Practices Guidelines for Journal Editors và Guidelines on Good Publication Practices.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Bản thảo bài báo chỉ được chấp nhận khi được tác giả chịu trách nhiệm chính cam kết các nội dung sau: Các nội dung của bản thảo chưa được đăng tải toàn bộ hoặc một phần ở các tạp chí khác; Tất cả các tác giả đều có đóng góp một cách đáng kể vào quá trình nghiên cứu hoặc chuẩn bị bản thảo và cùng chịu trách nhiệm về các nội dung của bản thảo; Tuân thủ các biện pháp đảm bảo đạo đức nghiên cứu (ví dụ thỏa thuận đồng ý tham gia nghiên cứu).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Cam kết bảo mật\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí cam kết thực hiện và tuân thủ các quy định của luật và các văn bản hướng dẫn liên quan đến bảo mật thông tin cá nhân trên không gian mạng. Các thông tin mà người dùng (tác giả, độc giả, biên tập viên, người phản biện) nhập vào các biểu mẫu trên Hệ thống Quản lý xuất bản trực tuyến của tạp chí chỉ được sử dụng vào các mục đích đã được tuyên bố rõ ràng và sẽ không được cung cấp cho bất kỳ bên thứ ba nào khác, hay dùng vào bất kỳ mục đích nào khác.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Phí gửi bài\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Lệ phí gửi đăng bài: 1.000.000đ\u002Fbài báo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Lệ phí gửi đăng nhanh: 1.500.000đ\u002Fbài báo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Đối với tác giả là cán bộ viên chức thuộc Trường Đại học Y Dược Cần Thơ thì được hỗ trợ 50% lệ phí gửi đăng bài.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Đối với sinh viên thực hiện đề tài nghiên cứu khoa học cấp trường được hỗ trợ 100% lệ phí đăng bài ( Tác giả gửi đính kèm “ Quyết định về việc giao tổ chức thực hiện đề tài nghiên cứu khoa học cấp Trường của sinh viên”).\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Hình thức nộp lệ phí:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Tiền mặt:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Nộp trực tiếp tại Phòng Tài chính - Kế toán, Trường Đại học Y Dược Cần Thơ, số 179 Nguyễn Văn Cừ, P. An Khánh, Q. Ninh Kiều, thành phố Cần Thơ.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Chuyển khoản:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tên Tài khoản: Trường ĐHYD Cần Thơ, Số TK: 0111000115668, tại ngân hàng Vietcombank chi nhánh Cần Thơ.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Thời gian: Áp dụng từ ngày 01\u002F02\u002F2023.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">* Phí gửi bài không được hoàn trả khi bài viết bị từ chối hoặc tác giả xin rút bài viết.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Quy trình phản biện bài báo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tạp chí Y Dược học Cần Thơ thực hiện quy trình phản biện kín hai chiều nghiêm ngặt. Danh tính của những người phản biện không được tiết lộ cho các tác giả và ngược lại. Quy trình thẩm định bài báo đăng gồm các bước sau:\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tiếp nhận bản thảo\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Tác giả liên hệ gửi bản thảo đến Tạp chí qua hệ thống trực tuyến tại website: https:\u002F\u002Ftapchi.ctump.edu.vn. Hướng dẫn về cách đăng ký, gửi bài và chuẩn bị bản thảo được cung cấp trên website của Tạp chí.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Sàng lọc sơ bộ\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Sau khi Tòa soạn nhận được bài báo của tác giả, Ban Thư ký sẽ tiến hành kiểm tra sơ bộ bài báo (các yêu cầu về nội dung và hình thức). Những bài báo không đúng quy cách hoặc có nội dung không phù hợp hoặc vi phạm bản quyền sẽ bị từ chối (Ban Thư ký thông báo phản hồi đến tác giả trong vòng 1 tuần). Những bài báo đủ điều kiện, được Ban Thư ký tòa soạn chuyển đến Ban Biên tập có cùng chuyên môn với nội dung bài báo để đề xuất người phản biện. Thời gian kể từ khi Ban Biên tập nhận bài báo đến khi đề xuất người phản biện bài báo chậm nhất là 5 ngày.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Vòng phản biện\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Ban Thư ký gửi bài và yêu cầu phản biện đến 02 phản biện độc lập.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Các phản biện gởi nhận xét cho Ban Thư ký. Thời gian từ khi gửi bài cho phản biện đến khi nhận ý kiến của phản biện tối đa là 20 ngày.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Xử ký kết quả phản biện\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Nếu ý kiến đồng ý cho đăng và không cần chỉnh sửa, Ban Thư ký tiếp tục đăng bài theo qui trình.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Nếu ý kiến đồng ý đăng và cần chỉnh sửa, Ban Thư ký sẽ thông tin đến tác giả chỉnh sửa theo yêu cầu của người phản biện. Thời gian chỉnh sửa và gửi lại kéo dài không quá 2 tuần, từ khi tác giả bài báo nhận được thông tin (Quá trình này có thể lặp lại tối đa 2 lần\u002F1 bài báo). Khi có sự thống nhất, đồng ý của người phản biện; bài báo được tiếp tục đăng theo qui trình.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">3. Những bài báo có chất lượng không đạt yêu cầu, cả 2 phản biện không đồng ý cho đăng sẽ bị Tòa soạn từ chối đăng.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">Xuất bản\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">1. Ban Thư ký tổng hợp các bản thảo đã được tác giả hoàn thiện sau thẩm định trình Ban Biên tập xem xét, Tổng Biên tập phê duyệt, quyết định bài đăng theo các tiêu chí: sự phù hợp nội dung với tôn chỉ và mục đích, thể loại bài viết (ưu tiên các bài có bài có nghiên cứu chuyên sâu, hàm lượng khoa học cao), đóng góp mới bài báo, bài báo được ưu tiên đăng trong số gần nhất của Tạp chí theo thứ tự: tính thời sự, chất lượng bài báo và thời gian gửi bài.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">2. Ban Biên tập và Ban Thư ký biên tập bản thảo, chế bản, đọc rà soát lỗi. Thời gian hoàn thành từ 10-15 ngày.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">3. Ban Thư ký có trách nhiệm thông báo cho tác giả bài báo (bằng e-mail) về tình hình phê duyệt bài báo, thời gian, số kỳ, tập xuất bản bài báo theo qui định.\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>\u003Cp>\u003Cspan style=\"color: rgb(0, 0, 0);\">4. Danh sách bài báo theo số Tạp chí được in ấn và phát hành trong năm định kỳ được công bố chính thức trên website: https:\u002F\u002Ftapchi.ctump.edu.vn\u003C\u002Fspan>\u003C\u002Fp>\u003Cp>\u003Cbr>\u003C\u002Fp>",{"VOID":490},"wcQ1uqwAAAAJ","2023-05-30T08:17:21.868+00:00",[],[494],{"id":495,"createTime":28,"updateTime":28,"relativeEntities":496,"slug":28,"properties":497,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":507,"parentIds":508,"statistic":28},"6413896b-eca9-442b-a73f-182a58a0ce40",[],{"title":498,"address":501,"country":504,"abbreviation":505},{"EN":499,"VI":500},"Can Tho University of Medicine and Pharmacy","Trường Đại học Y Dược Cần Thơ",{"EN":502,"VI":503},"No 179, Nguyen Van Cu street, An Khanh ward, Ninh Kieu district, Can Tho city, Vietnam","Số 179, đường Nguyễn Văn Cừ, phường An Khánh, quận Ninh Kiều, thành phố Cần Thơ, Việt Nam",{"VOID":15},{"VOID":506},"ctump","http:\u002F\u002Fwww.ctump.edu.vn\u002F",[],[],"https:\u002F\u002Ftapchi.ctump.edu.vn\u002Findex.php\u002Fctump",{"impactFactor":32,"impactFactorByYear":512,"i10Index":32,"i10IndexLast5Year":32,"totalPublication":514,"totalPublicationByYear":515,"totalCitation":520,"totalCitationByYear":521,"totalCitationPerPublication":108,"totalCitationPerPublicationByYear":523,"hindexLast5Year":45,"hindex":45},{"2022":513,"2023":111,"2024":106},0.01,1556,{"2020":47,"2021":516,"2022":517,"2023":518,"2024":519,"2025":122},57,306,801,358,161,{"2021":146,"2022":280,"2023":522},99,{"2021":524,"2022":318,"2023":104},0.23,{"impactFactor":28,"impactFactorByYear":28,"i10Index":123,"i10IndexLast5Year":123,"totalPublication":526,"totalPublicationByYear":527,"totalCitation":526,"totalCitationByYear":528,"totalCitationPerPublication":40,"totalCitationPerPublicationByYear":531,"hindexLast5Year":49,"hindex":49},476,{"0":205,"2019":123,"2021":139,"2022":459,"2023":451,"2024":357,"2025":49,"2026":48},{"2021":42,"2022":123,"2023":161,"2024":529,"2025":360,"2026":530},136,83,{"2021":105,"2022":513,"2023":532,"2024":127,"2025":533,"2026":534},0.62,25.43,13.83,{"id":536,"createTime":537,"updateTime":382,"relativeEntities":538,"slug":539,"properties":540,"entityType":25,"verifyStatus":26,"verifyTime":28,"verifyNote":28,"languages":552,"translateLanguages":28,"viewCount":133,"subjectFields":553,"manageAffiliations":554,"indexDatabases":555,"url":556,"thumbnailPath":557,"statistic":558,"gsStatistic":594,"type":55,"analyzePriority":28},"6984a56a-db70-403b-9cc4-4013e1ceaffa","2023-05-09T06:47:40.346+00:00",[],"T%E1%BA%A1p%20ch%C3%AD%20Nghi%C3%AAn%20c%E1%BB%A9u%20n%C6%B0%E1%BB%9Bc%20ngo%C3%A0i",{"country":541,"issn":542,"title":544,"introduce":547,"gsId":550},{"VOID":15},{"VOID":543},"25252445",{"EN":545,"VI":546},"VNU Journal of Foreign Studies","Tạp chí Nghiên cứu nước ngoài",{"EN":548,"VI":549},"{\"ops\":[{\"insert\":\"\\n\\nThe \\n\"},{\"attributes\":{\"italic\":true},\"insert\":\"VNU Journal of Science\"},{\"insert\":\"\\n was established in 1985 for the publication of national and international research papers in all fields of natural sciences and technology, social sciences and humanities. 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exact values of the Prokhorov metric for the set of probability distributions on a metric space is a challenging problem. In this paper probability distributions are approximated by finite-support distributions through optimal or quasi-optimal quantization, in such a way that exact calculation of the Prokhorov distance between a distribution and a quantizer can be performed. The exact value of the Prokhorov distance between two quantizers is obtained by solving an optimization problem through the Simplex method. This last value is used to approximate the Prokhorov distance between the two initial distributions, and the accuracy of the approximation is measured. We illustrate the method on various univariate and bivariate probability distributions. Approximation of bivariate standard normal distributions by quasi-optimal quantizers is also considered.",{"EN":990},"Calculation of the Prokhorov distance by optimal quantization and maximum flow",{"VOID":992},"Dudley, R.M.: Distances of probability measures and random variables. Ann. Math. Stat. 39, 1563–1572 (1968)\nGarcia-Palomares, U., Giné, E.: On the linear programming approach to the optimality property of Prokhorov’s distance. J. Math. Anal. Appl. 60, 596–600 (1977)\nGuéret, C., Prins, C., Sevaux, M.: Application of optimization with Xpress-MP. Translated and revised by S. Heipcke from “Programmation Linéaire” (2000). Éditions Eyrolles, Paris, France. Dash Optimization Ltd (2002)\nHampel, F.: A general qualitative definition of robustness. Ann. Math. Stat. 42, 1887–1896 (1971)\nHampel, F., Ronchetti, E.M., Rousseeuw, P.J., Stahel, W.A.: Robust Statistics. The Approach Based on Influence Functions. Wiley, New York (1986)\nHoaglin, D.C., Mosteller, F., Tukey, J.W.: Understanding Robust and Exploratory Data Analysis. Wiley, New York (1983)\nHuber, P.J.: Robust Statistics. Wiley, New York (1981)\nProkhorov, Y.: Convergence of random processes and limit theorems in probability theory. Theory Probab. Appl. 1, 157–214 (1956)\nSchay, G.: Nearest random variables with given distributions. Ann. Probab. 2, 163–166 (1974)",{"VOID":994},"10.1007\u002Fs10182-008-0082-1","PUBLICATION","Auto Verify","http:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs10182-008-0082-1",[999,1015],{"id":1000,"sortIndex":32,"researcher":28,"roles":1001,"affiliations":1003,"properties":1012,"displayName":1014,"givenName":28,"familyName":28},"1bab0eb6-9d7e-4924-ae3a-0abc50a95142",[1002],"AUTHOR",[1004],{"id":1005,"sortIndex":32,"affiliation":1006,"properties":28},"d26ba074-1bb0-407a-9fd5-8a62f70ecc32",{"id":1005,"createTime":28,"updateTime":28,"relativeEntities":1007,"slug":28,"properties":1008,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1011,"statistic":28},[],{"title":1009},{"VI":1010},"Mathematical Institute of Toulouse (UPS) and ENSEEIHT, Toulouse Cédex 7, France",[],{"title":1013},{"VI":1014},"Bernard 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subjective assessment of quality of life, personal skills and the agreement with a certain opinion are common issues in clinical, social, behavioral and marketing research. A wide set of surveys providing ordinal data arises. Beside such variables, other common surveys generate responses on a continuous scale, where the variable actual point value cannot be observed since data belong to certain groups. This paper introduces a re-formalization of the recent “Monotonic Dependence Coefficient” (MDC) suitable to all frameworks in which, given two variables, the independent variable is expressed in ordinal categories and the dependent variable is grouped. We denote this novel coefficient with \n                  \n                    \n                  \n                  $$\\mathrm{MDC}\\mathrm{go}$$\n                  \n                    \n                  \n                . The \n                  \n                    \n                  \n                  $$\\mathrm{MDC}\\mathrm{go}$$\n                  \n                    \n                  \n                 behavior and the scenarios in which it presents better performance with respect to the alternative correlation\u002Fassociation measures, such as Spearman’s \n                  \n                    \n                  \n                  $$r_\\mathrm{S}$$\n                  \n                    \n                  \n                , Kendall’s \n                  \n                    \n                  \n                  $$\\tau _b$$\n                  \n                    \n                  \n                 and Somers’ \n                  \n                    \n                  \n                  $$\\varDelta $$\n                  \n                    \n                  \n                 coefficients, are explored through a Monte Carlo simulation study. Finally, to shed light on the usefulness of the proposal in real surveys, an application to drug-expenditure data is considered.",{"EN":1113},"MDCgo takes up the association\u002Fcorrelation challenge for grouped ordinal data",{"VOID":1115},"Agresti, A.: Analysis of Ordinal Categorical Data, 2nd edn. Wiley, New York (2010)\nAhrens, W., Pigeot, I.: Handbook of Epidemiology. Springer, Berlin, Heidelberg (2005)\nAimar, F.: Local reimbursed pharmaceutical expenditure monitoring through the use of statistical tools. Ph.D. Dissertation Thesis, University of Turin (2012)\nBernardini, A.C., Spandonaro, F.: Pharmaceutical Assistance: access to innovation, sustainability and selectivity. 10th Health Report, Chapter 9 (in Italian) (2014)\nBlitz, R.C., Brittain, J.A.: An extension of the Lorenz diagram to the correlation of two variables. Metron XXIII(1–4), 137–143 (1964)\nDenuit, M., Lambert, P.: Constraints on concordance measures in bivariate discrete data. J. Multivar. Anal. 93, 40–57 (2005)\nFerrari, P.A., Raffinetti, E.: A different approach to Dependence Analysis. Multivar. Behav. Res. 50(2), 248–264 (2015)\nGoodman, L.A., Kruskal, W.H.: Measures of association for cross classifications. J. Am. Stat. Assoc. 49, 732–764 (1954)\nHofert, M.: On sampling from the multivariate \\(t\\) distribution. R J. 5(2), 129–136 (2013)\nJonckheere, A.R.: A distribution-free \\(k\\)-sample. Tests against ordered alternatives. Biometrika 41, 133–145 (1954)\nKendall, K.: New measure of rank correlation. Biometrika 30(1–2), 81–89 (1938)\nLikert, R.: A technique for the measurement of attitudes. Arch. Psychol. 22(140), 5–55 (1932)\nLorenz, M.O.: Methods of measuring the concentration of wealth. Publ. Am. Stat. Assoc. 9(70), 209–219 (1905)\nMartin, J., Gonzales, M.P.L., Garcia, D.C.: Review of the literature of the determinants of healthcare expenditure. Appl. Econ. 43, 19–46 (2011)\nMarshall, A.W., Olkin, I., Arnold, C.A.: Inequalities: Theory of Majorization and Its Applications, 2nd edn. Springer, Berlin (2011)\nNorman, G.: Likert scales, levels of measurement and the law of statistics. Adv. Health Sci. Educ. 15, 625–632 (2010)\nOECD: Estimating expenditure by disease, age and gender under the system of health accounts (SHA) framework. Final report. http:\u002F\u002Fwww.oecd.org\u002Fels\u002Fhealth-systems\u002FEstimatingExpenditurebyDiseaseAgeandGender_FinalReport.pdf (2008). Accessed 15 Mar 2017\nOwens, G.M.: Gender differences in health care expenditures, resource utilization, and quality of care. J. Manag. Care Pharm. 14(3 Suppl), 2–6 (2008)\nPearson, K.: Mathematical contributions to the theory of evolution–XVI. In: Pearson, K. (ed.) On Further Methods for Determining Correlation. Draper’s Company Research Memoirs, Biometric Series, vol. IV. Cambridge University Press, Cambridge pp. 1–39 (1907)\nRodgers, J.L., Nicewander, W.A.: Thirteen ways to look at the correlation coefficient. Am. Stat. 42(1), 59–66 (1988)\nRoth, M.: On the multivariate t distribution. Report no.: LiTH-ISY-R-3059 (2013)\nSchezhtman, E., Yitzhaki, S.: A measure of association based on Gini’s mean difference. Commun. Stat. Theory Methods 16(1), 207–231 (1987)\nSomers, R.H.: A new asymmetric measure of association for ordinal variables. Am. Sociol. Rev. 27, 799–811 (1962)\nStuart, A.: The estimation and comparison of strengths of association in contingency tables. Biometrika 40, 105–110 (1953)\nSpearman, C.: The proof and measurement of correlation between two things. Am. J. Psychol. 15, 72–101 (1904)\nTerpstra, T.J.: The asymptotic normality and consistency of Kendall’s test against trend, when ties are present in one ranking. 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paper gives conditions for the consistency of simultaneous redescending M-estimators for location\n   and scale. The consistency postulates the uniqueness of the parameters μ and σ, which are defined\n   analogously to the estimations by using the population distribution function instead of the empirical\n   one. The uniqueness of these parameters is no matter of course, because redescending ψ- and χ-functions,\n   which define the parameters, cannot be chosen in a way that the parameters can be considered as\n   the result of a common minimizing problem where the sum of ρ-functions of standardized residuals\n   is to be minimized. The parameters arise from two minimizing problems where the result of one problem\n  is a parameter of the other one. This can give different solutions. Proceeding from a symmetrical\n  unimodal distribution and the usual symmetry assumptions for ψ and χ leads, in most but not\n  in all cases, to the uniqueness of the parameters. Under this and some other assumptions, we can also\n  prove the consistency of the according M-estimators, although these estimators are usually not unique\n  even when the parameters are. The present article also serves as a basis for a forthcoming\n  paper, which is concerned with a completely outlier-adjusted confidence interval for μ. So\n  we introduce a ñ where data points far away from the bulk of the data are not counted at\n  all.\n ",{"EN":1238},"Consistency of completely outlier-adjusted simultaneous redescending M-estimators of location and scale",{"VOID":1240},"Bachmaier, M. (2000) Klassische, robuste und nichtparametrische Bartlett-Tests und robuste Varianzanalyse bei heterogenen Skalenparametern. Shaker Verlag, Aachen\nClarke, B. (1991) The selection funktional. Probability and Mathematical Statistics 11, 149–156\nHampel, F.R., Rousseeuw, P.J., Ronchetti, E.M., Stahel, W.A. (1986) Robust Statistics. John Wiley & Sons, New York\nHuber, P.J. (1977) Robust Statistical Procedures. Regional Conference Series in Applied Mathematics 27, Society for Industrial and Applied Mathematics, Philadelphia, Pennsylvania\nHuber, P.J. (1981) Robust Statistics. John Wiley & Sons, New York\nFreedman, D.A., Diaconis, P. (1982) On inconsistent M-estimators. The Annals of Statistics 10, 454–461\nKent, J.T., Tyler, D.E. (1996) Constrained M-estimation for multivariate location and scatter. The Annals of Statistics 24, 1346–1370\nKent, J.T., Tyler, D.E. (2001) Regularity and uniqueness for constrained M-estimates and redescending M-estimates. The Annals of Statistics 29, 252–265\nJureckova, J., Sen, P.K. (1996) Robust Statistical Procedures. Asymptotics and Interrelations. John Wiley & Sons, New York\nMarazzi, A. (1993) Algorithms, Routines and S Functions for Robust Statistics. The Fortran Library ROBETH with an Interface to S-Plus. Wadsworth & Brooks\u002FCole Advanced Books & Software, Pacific Grove, California\nRousseeuw, P.R., Leroy, A.M. (2003) Robust Regression and Outlier Detection. John Wiley & Sons, New York\nTatsuoka, K., Tyler, D.E. (2000) On the uniqueness of S-Functionals and M-Functionals under nonelliptical distributions. The Annals of Statistics 28, 1219–1243",{"VOID":1242},"10.1007\u002Fs10182-007-0023-4","http:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs10182-007-0023-4",[1245],{"id":1246,"sortIndex":32,"researcher":28,"roles":1247,"affiliations":1248,"properties":1257,"displayName":1259,"givenName":28,"familyName":28},"48820b81-e6b3-46ff-89bd-3fd8e2964354",[1002],[1249],{"id":1250,"sortIndex":32,"affiliation":1251,"properties":28},"9592820f-7cd3-4c0d-9d72-0235a7908df6",{"id":1250,"createTime":28,"updateTime":28,"relativeEntities":1252,"slug":28,"properties":1253,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1256,"statistic":28},[],{"title":1254},{"VI":1255},"Fachgebiet Technik im Pflanzenbau, Technische Universität München, Freising, Germany",[],{"title":1258},{"VI":1259},"Martin 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consider the problem of estimating the conditional quantile of a time series \n                  \n                    \n                  \n                  $$\\{ Y_t\\}$$\n                  \n                    \n                  \n                 at time \n                  \n                    \n                  \n                  $$t$$\n                  \n                    \n                  \n                 given covariates \n                  \n                    \n                  \n                  $$\\varvec{X}_{t}$$\n                  \n                    \n                  \n                , where \n                  \n                    \n                  \n                  $$\\varvec{X}_{t}$$\n                  \n                    \n                  \n                 can be either exogenous variables or lagged variables of \n                  \n                    \n                  \n                  $${ Y_t}$$\n                  \n                    \n                  \n                 . The conditional quantile is estimated by inverting a kernel estimate of the conditional distribution function, and we prove its asymptotic normality and uniform strong consistency. The performance of the estimate for light and heavy-tailed distributions of the innovations is evaluated by a simulation study. Finally, the technique is applied to estimate VaR of stocks in DAX, and its performance is compared with the existing standard methods using backtesting.",{"EN":1341},"Nonparametric estimates for conditional quantiles of time series",{"VOID":1343},"Abberger, K.: Nichtparametrische Schaetzung bedingter Quantile in Zeitreihen - Mit Anwendung auf Finanzmarktdaten. Hartung-Gore Verlag, Konstanz (1996)\nBerkowitz, J., Christoffersen, P., Pelletier, D.: Evaluating value-at-risk models with desk-level data, Working Paper 010, North Carolina State University, Department of Economics (2009)\nBickel, P.J., Lehmann, E.: Descriptive statistics for nonparametric models. III: Dispersion. Ann. Statist. 4, 1139–1159 (1976)\nBoente, G., Fraiman, R.: Asymptotic distribution of smoothers based on local means and local medians under dependence. J. Multivar. Anal. 54, 77–90 (1995)\nBosq, D.: Nonparametric statistics for stochastic processes. Springer (1996)\nCai, Z.: Regression quantiles for time series. Econom. Theory 18(01), 169–192 (2002)\nCai, Z., Wang, X.: Nonparametric method for estimating conditional value-at-risk and expected shorfall. J. Econom. 147, 120–130 (2008)\nCarbon, M.: Bernstein’s inequality for strong mixing, non-stationary processes: applications. C. R. Acad. Sci. Paris I(297), 303–306 (1983)\nCollomb, G., Härdle, W.: Strong uniform convergence rates in robust nonparametric time series analysis and prediction: kernel regression estimation from dependent observations. Stoch. Process. Appl. 23, 77–89 (1986)\nEngle, R., Manganelli, S.: CAViaR: conditional autoregressive value at risk by regression quantiles. J. Bus. Econ. Stat. 22, 367–381 (2004)\nFan, J., Gijbels, I.: Local Polynomial Modelling and its Applications—Theory and Methodologies. Chapman and Hall, New York (1995)\nGyörfi, L., Härdle, W., Sarda, P., Vieu, P.: Nonparametric curve estimation from time series. In: Lecture Notes in Statistics. Springer, Heidelberg (1989)\nHärdle, W., Lütkepohl, H., Chen, R.: A review of nonparametric time series analysis. Int. Stat. Rev. 65, 49–72 (1997)\nHall, P., Yao, Q.: Inference in ARCH and GARCH models with heavy-tailed errors. Econometrica 71, 285–317 (2003)\nHall, P., Wolff, R., Yao, Q.: Methods for estimating a conditional distribution function. J. Am. Stat. Assoc. 94, 154–163 (1999)\nHorvath, L., Yandell, B.: Asymptotics of conditional empirical processes. J. Multivar. Anal. 26, 184–206 (1988)\nHuber, P.J.: Robust Statistics. Wiley, New York (1981)\nJorion, P.: Value-at-Risk: The New Benchmark for Managing Financial Risk, vol. 2. McGraw-Hill, New York (2000)\nKoenker, R., Bassett, G.: Regression quantiles. Econometrica 46, 33–50 (1978)\nKoenker, R.: Galton, Edgeworth, Frisch and prospects for quantile regression in econometrics. J. Econom. 95, 347–374 (1999)\nLopez, J.A., Walter, C.: Evaluating covariance matrix forecasts in a value-at-risk framework. J. Risk 3, 69–98 (2001)\nMasry, E., Tjostheim, D.: Nonparametric estimation and identification of nonlinear \\(ARCH\\) time series: strong convergence and asymptotic normality. Econom. Theory 11, 258–289 (1995)\nMasry, E., Tjostheim, D.: Additive nonlinear \\(ARX\\) time series and projection estimates. Econom. Theory 13, 214–252 (1997)\nMwita, P.: Semiparametric Estimation of Conditional Quantiles for Time Series with Applications in Finance. Ph.D. Thesis, University of Kaiserslautern (2003)\nNadaraya, E.A.: On estimating regression. Theory Probab. Appl. 9, 141–142 (1964)\nRama Krishnaiah Y.S.: On the Glivenko–Cantelli theorem for generalized empirical processes based on strong mixing sequences Stat. Probab. Lett. 47(7), 2863–2875 (1990)\nSpokoiny, V., Wang, W., Hrdle W.: Local quantile regression. J. Stat. Plann. Inference 143(7), with discussions, 1109–1129 (2013)\nTruong, Y.K., Stone, C.J.: Nonparametric function estimation involving time series. Ann. Stat. 20, 77–97 (1992)\nWatson, G.S.: Smooth regression analysis. Sankya Ser. A 26, 359–372 (1964)\nWeiss, A.A.: ARMA models with ARCH errors. J. Time Ser. Anal. 3, 129–143 (1984)",{"VOID":1345},"10.1007\u002Fs10182-014-0234-4","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10182-014-0234-4",[1348,1363,1376],{"id":1349,"sortIndex":32,"researcher":28,"roles":1350,"affiliations":1351,"properties":1360,"displayName":1362,"givenName":28,"familyName":28},"b76837b8-36f3-4ef3-9297-c147d7300fd7",[1002],[1352],{"id":1353,"sortIndex":32,"affiliation":1354,"properties":28},"085c99b5-9d27-4ad0-a2d7-24049fdc03b2",{"id":1353,"createTime":28,"updateTime":28,"relativeEntities":1355,"slug":28,"properties":1356,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1359,"statistic":28},[],{"title":1357},{"VI":1358},"Hermann Otto Hirschfeld Junior Professor at the Ladislaus von Bortkiewicz Chair of Statistics and C.A.S.E., Humboldt-Universität zu Berlin,  Berlin, Germany",[],{"title":1361},{"VI":1362},"Jürgen 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Sci. 33(2), 160–183 (2017). arXiv:1702.00971\nBrauns, H., Scherer, S., Steinmann, S.: The CASMIN educational classification in international comparative research. In: Hoffmeyer-Zlotnik, J.H.P., Wolf, C. (eds.) Advances in Cross-National Comparison: A European Working Book for Demographic and Socio-Economic Variables, pp. 221–244. Springer (2003)\nChristensen, R.H.B.: ordinal: Regression Models for Ordinal Data [Computer software manual] (2019). Retrieved from https:\u002F\u002FCRAN.R-project.org\u002Fpackage=ordinal (R package version 2019.12–10)\nEnders, C.K., Keller, B.T., Levy, R.: A fully conditional specification approach to multilevel imputation of categorical and continuous variables. Psychol Methods (2017)\nGalimard, J.E., Chevret, S., Curis, E., Resche-Rigon, M.: Heckman imputation models for binary or continuous mnar outcomes and mar predictors. BMC Med. Res. Methodol. 18(1), 90 (2018)\nGalimard, J.-E., Chevret, S., Protopopescu, C., Resche-Rigon, M.: Imputation of MNAR missing data using one-step ML selection model. In: 36th Annual Conference of the International Society for Clinical Biostatistics (2015)\nGalimard, J.-E., Chevret, S., Protopopescu, C., Resche-Rigon, M.: A multiple imputation approach for MNAR mechanisms compatible with Heckman’s model. Stat. Med. (2016)\nGelman, A., Carlin, J., Stern, H., Dunson, D., Vehtari, A., Rubin, D.: Bayesian Data Analysis. Chapman & Hall\u002FCRC (2013)\nGoldfarb, D.: A family of variable-metric methods derived by variational means. Math. Comput. 24(109), 23–26 (1970)\nGolub, G.H., Welsch, J.H.: Calculation of Gauss quadrature rules. Math. Comput. 23(106), 221–230 (1969)\nGreene, W.H.: Econometric Analysis. Pearson (2012)\nHammon, A., Zinn, S.: Multiple imputation of binary multilevel missing not at random data. J. Roy. Stat. Soc.: Ser. C (Appl. Stat.) 69(3), 547–564 (2020)\nLittle, R.: A test of missing completely at random for multivariate data with missing values. J. Am. Stat. Assoc. 83, 1198–1202 (1988)\nLiu, Q., Donald, A.P.: A note on Gauss-Hermite quadrature. Biometrika 81(3), 624–629 (1994)\nLüdtke, O., Robitzsch, A., Grund, S.: Multiple imputation of missing data in multilevel designs: A comparison of different strategies. Psychol. Methods 22(1), 141 (2017)\nMolenberghs, G., Fitzmaurice, G.: Longitudinal data analysis. In: Fitzmaurice, G., Davidian, M., Verbeke, G., Molenberghs, G. (Eds.), Chapman & Hall\u002FCRC, Boca Raton, pp. 395-408 (2008)\nNaylor, J.C., Smith, A.F.M.: Applications of a method for the efficient computation of posterior distributions. J. Roy. Stat. Soc.: Ser. C (Appl. Stat.) 31(3), 214–225 (1982)\nNocedal, J., Wright, S.: Numerical Optimization. Springer, Berlin (2006)\nR Core Team.: R: A language and environment for statistical computing [Computer software manual]. Vienna, Austria (2020). Retrieved from https:\u002F\u002Fwww.R-project.org\u002F\nRaghunathan, T.E., Lepkowski, J.M., Van Hoewyk, J., Solenberger, P.: A multivariate technique for multiply imputing missing values using a sequence of regression models. Surv. Methodol. 27(1), 85–96 (2001)\nRendtel, U.: On the Choice of a Selection-Model When Estimating Regressionmodels with Selectivity (Discussion Papers of DIW Berlin). DIW Berlin, German Institute for Economic Research (1992)\nRobitzsch, A., Grund, S.: miceadds: Some Additional Multiple Imputation Functions, Especially for ‘mice’ [Computer software manual] (2020). Retrieved from https:\u002F\u002FCRAN.R-project.org\u002Fpackage=miceadds (R package version 3.10–28)\nRubin, D.B.: Inference and missing data. Biometrika 63(3), 581–592 (1976)\nRubin, D.B.: Multiple Imputation for Nonresponse in Surveys. Wiley, New York (1987)\nSchneider, E.: Von der Hauptschule in die Sekundarstufe II: eine schülerbiografische Längsschnittstudie (Vol. 67). Springer (2018)\nVan Buuren, S.: Flexible Imputation of Missing Data. CRC Press (2018)\nVan Buuren, S., Brand, J.P., Groothuis-Oudshoorn, C.G.M., Rubin, D.B.: Fully conditional specification in multivariate imputation. J. Stat. Comput. Simul. 76(12), 1049–1064 (2006)\nVan Buuren, S.: Multiple imputation of discrete and continuous data by fully conditional specification. Stat. Methods Med. Res. 16(3), 219–242 (2007)\nVan Buuren, S., Groothuis-Oudshoorn, K.: mice: Multivariate imputation by chained equations in. J. Stat. Softw. 45(3), 1–67 (2011)\nVon Hippel, P.T.: Regression with missing ys: An improved strategy for analyzing multiply imputed data. Sociol. Methodol. 37(1), 83–117 (2007)\nWarm, T.A.: Weighted likelihood estimation of ability in item response theory. Psychometrika 54, 427–450 (1989)\nWößmann, L.: Fundamental determinants of school efficiency and equity: German states as a microcosm for oecd countries (IZA Discussion Paper No. No. 2880). IZA Insititute of Labor Economics (2007)\nZhu, J., Raghunathan, T.E.: Convergence Properties of a Sequential Regression Multiple Imputation Algorithm. J. Am. Stat. Assoc. 110(511), 1112–1124 (2015)\nZinn, S., Würbach, A., Steinhauer, H.W., Hammon, A.: Attrition and selectivity of the NEPS starting cohorts: An overview of the past 8 years. AStA Wirtschaftsund Sozialstatistisches Archiv, 1–44 (2020)",{"VOID":1646},"10.1007\u002Fs10182-022-00461-9","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10182-022-00461-9",[1649],{"id":1650,"sortIndex":32,"researcher":28,"roles":1651,"affiliations":1652,"properties":1670,"displayName":1672,"givenName":28,"familyName":28},"b747b8f5-b7c1-428b-b78c-1dd7fbb20bd4",[1002],[1653,1661],{"id":1654,"sortIndex":32,"affiliation":1655,"properties":28},"819113fd-64d9-4615-b917-f4d8ced55930",{"id":1654,"createTime":28,"updateTime":28,"relativeEntities":1656,"slug":28,"properties":1657,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1660,"statistic":28},[],{"title":1658},{"VI":1659},"German Institute for Economic Research (DIW Berlin), Berlin, 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Hammon",{"url":1647,"publisher":1674,"properties":1736},{"id":868,"createTime":869,"updateTime":870,"relativeEntities":1675,"slug":872,"properties":1676,"entityType":25,"verifyStatus":882,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":32,"subjectFields":1680,"manageAffiliations":1705,"indexDatabases":1716,"url":28,"thumbnailPath":28,"statistic":1731,"gsStatistic":28,"type":55,"analyzePriority":28},[],{"issn":1677,"title":1678,"eissn":1679},{"VOID":877},{"EN":879},{"VOID":875},[1681,1685,1689,1693,1697,1701],{"id":909,"createTime":28,"updateTime":28,"relativeEntities":1682,"label":1683,"description":1684,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":912},{},{"id":885,"createTime":28,"updateTime":28,"relativeEntities":1686,"label":1687,"description":1688,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":888},{},{"id":891,"createTime":28,"updateTime":28,"relativeEntities":1690,"label":1691,"description":1692,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":894},{},{"id":897,"createTime":28,"updateTime":28,"relativeEntities":1694,"label":1695,"description":1696,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":900},{},{"id":903,"createTime":28,"updateTime":28,"relativeEntities":1698,"label":1699,"description":1700,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":906},{},{"id":915,"createTime":28,"updateTime":28,"relativeEntities":1702,"label":1703,"description":1704,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":918},{},[1706,1711],{"id":922,"createTime":28,"updateTime":28,"relativeEntities":1707,"slug":28,"properties":1708,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1710,"statistic":28},[],{"title":1709},{"EN":926},[928],{"id":930,"createTime":28,"updateTime":28,"relativeEntities":1712,"slug":28,"properties":1713,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1715,"statistic":28},[],{"title":1714},{"EN":934},[],[1717,1724],{"id":938,"indexDatabase":1718,"url":950,"indexYears":28,"academicFieldIds":1723,"indexDatabaseRanking":28},{"id":940,"createTime":28,"updateTime":28,"relativeEntities":1719,"label":1720,"description":1721,"key":947,"publicationTags":1722,"standard":28},[],{"EN":943,"VI":943},{"EN":945,"VI":946},[949,813],[952],{"id":954,"indexDatabase":1725,"url":960,"indexYears":961,"academicFieldIds":1730,"indexDatabaseRanking":969},{"id":775,"createTime":28,"updateTime":28,"relativeEntities":1726,"label":1727,"description":1728,"key":781,"publicationTags":1729,"standard":28},[],{"EN":778,"VI":778},{"EN":778,"VI":780},[783],[963,964,965,966,967,968],{"impactFactor":32,"impactFactorByYear":1732,"i10Index":32,"i10IndexLast5Year":32,"totalPublication":972,"totalPublicationByYear":1733,"totalCitation":32,"totalCitationByYear":1734,"totalCitationPerPublication":32,"totalCitationPerPublicationByYear":1735,"hindexLast5Year":32,"hindex":32},{},{"2007":122,"2008":133,"2009":49,"2010":47,"2011":136,"2012":205,"2013":47,"2014":49,"2015":127,"2016":145,"2017":323,"2018":199,"2019":205,"2020":51,"2021":134,"2022":199,"2023":127,"2024":48},{},{},{"pages":1737,"volume":1739},{"VOID":1738},"671-692",{"VOID":1740},"107","2022-08-22",2022,[969,949],{"id":1745,"createTime":1746,"updateTime":1746,"relativeEntities":1747,"slug":28,"properties":1748,"entityType":995,"verifyStatus":882,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":32,"primaryUrl":1757,"fullTextUrl":28,"authors":1758,"publicationType":1030,"publisherRelationship":1802,"citationCount":28,"citationInfo":28,"publishDate":1869,"publishYear":1329,"citationAnalyzeStatus":882,"lastCitationAnalyze":28,"indexDatabases":1870,"openAccess":28,"references":28,"isForceReanalyzing":1102},"052da36e-d6bb-4c59-bc47-72d735e1fd8a","2024-01-05T04:36:21.683+00:00",[],{"abstract":1749,"title":1751,"references":1753,"doi":1755},{"EN":1750},"The multinomial logit model (MNL) is one of the most frequently used statistical models in marketing\n  applications. It allows one to relate an unordered categorical response variable, for example representing\n  the choice of a brand, to a vector of covariates such as the price of the brand or variables characterising\n  the consumer. In its classical form, all covariates enter in strictly parametric, linear form into the\n  utility function of the MNL model. In this paper, we introduce semiparametric extensions, where smooth\n  effects of continuous covariates are modelled by penalised splines. A mixed model representation of\n  these penalised splines is employed to obtain estimates of the corresponding smoothing parameters, leading\n  to a fully automated estimation procedure. To validate semiparametric models against parametric models,\n  we utilise different scoring rules as well as predicted market share and compare parametric and semiparametric\n  approaches for a number of brand choice data sets.\n ",{"EN":1752},"Semiparametric multinomial logit models for analysing consumer choice behaviour",{"VOID":1754},"Abe, M. (1998) Measuring consumer nonlinear brand choice response to price. Journal of Retailing 74, 541–568\nAbe, M. (1999) A generalized additive model for discrete-choice data. Journal of Business and Economic Statistics 17, 271–284\nAbe, M., Boztug, Y., Hildebrandt, L. (2004) Investigating the competitive assumption of multinomial logit models of brand choice by nonparametric modelling. Computational Statistics 19, 635–657\nAilawadi, K.L., Gedenk, K., Neslin, S.A. (1999) Heterogeneity and purchase event feedback in choice models: An empirical comparison with implications for model building. International Journal of Research in Marketing 16, 177–198\nBen Akiva, M., Lerman, S.L. (1985) Discrete Choice Analysis: Theory and Application to Travel Demand. The MIT Press, Cambridge, MA\nBlattberg, R.C., Neslin, S.A. (1990) Sales Promotion: Concepts, Methods and Strategies. Prentice Hall, Englewood Cliffs, NJ\nBrezger, A., Lang, S. (2006) Generalized additive regression based on Bayesian P-splines. Computational Statistics and Data Analysis 50, 967–991\nBrezger, A., Steiner, W. (2007) Monotonic spline regression to estimate promotional price effects: A comparison to benchmark parametric models. Journal of Business and Economic Statistics, to appear\nCurrie, I.D., Durban, M., Eilers, P.H.C. (2006) Generalized linear array models with applications to multidimensional smoothing. Journal of the Royal Statistical Society, Series B 68, 259–280\nEilers, P.H.C., Marx, B.D. (1996) Flexible smoothing using B-splines and penalties (with comments and rejoinder). Statistical Science 11, 89–121\nFahrmeir, L., Tutz, G. (2001) Multivariate Statistical Modelling Based on Generalized Linear Models. New York: Springer\nFahrmeir, L., Kneib, T., Lang, S. (2004) Penalized structured additive regression: A Bayesian perspective. Statistica Sinica 14, 731–761\nGneiting, T., Raftery, A.E. (2007) Strictly proper scoring rules, prediction, and estimation. Journal of the American Statistical Association 102, 359–378\nGuidagni, P.M., Little, J.D.C. (1983) A logit model of brand choice calibrated on scanner data. Marketing Science 11, 372–385\nHelson, H. (1964) Adaptation-Level Theory. Harper & Row, New York, London\nKahnemann, D., Tversky, A. (1979) A prospect theory: An analysis of decisions under risk. Econometrica 47, 263–291\nKalwani, M.U., Yim, C.K., Rinne, H.J., Sugita Y. (1990) A price expectations model of customer brand choice. Journal of Marketing Research 27, 251–262\nKalyanaram, G., Little, J.D.C. (1994) An empirical analysis of latitude of price acceptance in consumer package goods. Journal of Consumer Research 21, 408–418\nKauermann, G. (2005) A note on smoothing parameter selection for penalised spline smoothing. Journal of Statistical Planing and Inference 127, 53–69\nKauermann, G. (2006) Nonparametric models and their estimation. Allgemeines Statistisches Archiv 90, 135–150\nKauermann, G., Khomski, P. (2006) Additive two way hazards model with varying coefficients. Computational Statistics and Data Analysis 51, 1944–1956\nKneib, T., Fahrmeir, L. (2006) Structured additive regression for categorical space-time data: A mixed model approach. Biometrics 62, 109–118\nKneib, T., Fahrmeir, L. (2007) A mixed model approach for geoadditive hazard regression. Scandinavian Journal of Statistics 34, 207–228\nKrishnamurthi, L., Raj, S.P. (1988) A model of brand choice and purchase quantity price sensitivities. Marketing Science 7, 1–20\nKrivobokova, T., Crainiceanu, C.M., Kauermann, G. (2006) Fast Adaptive Penalized Splines. Johns Hopkins University, Dept. of Biostatistics Working Papers. Working Paper 100\nLin, X., Zhang, D. (1999) Inference in generalized additive mixed models by using smoothing splines. Journal of the Royal Statistical Society, Series B 61, 381–400\nMcFadden, D. (1974) Conditional logit analysis of qualitative choice behavior. Frontiers in Econometrics, Zarembka, P. (ed.), 105–142, Academic Press, New York London\nMcFadden, D. (1980) Econometric models for probabilistic choice among Products. Journal of Business 53, 13–34\nRuppert, D., Wand, M.P., Carroll, R.J. (2003) Semiparametric Regression. Cambridge University Press, Cambridge\nSherif, M., Hovland, C.I. (1961) Social Judgement. Yale University Press, New Haven London\nSteinberger, M. (2001) Multinomiale Logitmodelle mit linearen Splines zur Analyse der Markenwahl. Peter Lang, Frankfurt Berlin\nTellis, G.J. (1988) Advertising exposure, loyalty and brand purchase: a two-stage model of choice. Journal of marketing research 25, 134–144\nWedel, M., Leeflang, P.S.H. (1998) A model for the effects of psychological pricing in Gabor-Granger price studies. Journal of Economic Psychology 19, 237–260",{"VOID":1756},"10.1007\u002Fs10182-007-0033-2","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10182-007-0033-2",[1759,1774,1789],{"id":1760,"sortIndex":32,"researcher":28,"roles":1761,"affiliations":1762,"properties":1771,"displayName":1773,"givenName":28,"familyName":28},"4acf317f-e67b-467e-bb84-c70d23a2df97",[1002],[1763],{"id":1764,"sortIndex":32,"affiliation":1765,"properties":28},"c13a2584-88f9-4f39-b7c8-5038f4beb28b",{"id":1764,"createTime":28,"updateTime":28,"relativeEntities":1766,"slug":28,"properties":1767,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1770,"statistic":28},[],{"title":1768},{"VI":1769},"Department of Statistics, Ludwig-Maximilians-University, Munich, Germany",[],{"title":1772},{"VI":1773},"Thomas Kneib",{"id":1775,"sortIndex":40,"researcher":28,"roles":1776,"affiliations":1777,"properties":1786,"displayName":1788,"givenName":28,"familyName":28},"7caa8fcf-e490-41fc-a155-e8d2c90d7336",[1002],[1778],{"id":1779,"sortIndex":32,"affiliation":1780,"properties":28},"4aa9eaa6-930e-49b1-9e0e-346074dc7aa2",{"id":1779,"createTime":28,"updateTime":28,"relativeEntities":1781,"slug":28,"properties":1782,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1785,"statistic":28},[],{"title":1783},{"VI":1784},"University of Regensburg, Regensburg, Germany",[],{"title":1787},{"VI":1788},"Bernhard Baumgartner",{"id":1790,"sortIndex":123,"researcher":28,"roles":1791,"affiliations":1792,"properties":1799,"displayName":1801,"givenName":28,"familyName":28},"e45536d8-9e1a-4db6-9ee6-d576b296b172",[1002],[1793],{"id":1779,"sortIndex":32,"affiliation":1794,"properties":28},{"id":1779,"createTime":28,"updateTime":28,"relativeEntities":1795,"slug":28,"properties":1796,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1798,"statistic":28},[],{"title":1797},{"VI":1784},[],{"title":1800},{"VI":1801},"Winfried J. Steiner",{"url":1757,"publisher":1803,"properties":1865},{"id":868,"createTime":869,"updateTime":870,"relativeEntities":1804,"slug":872,"properties":1805,"entityType":25,"verifyStatus":882,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":32,"subjectFields":1809,"manageAffiliations":1834,"indexDatabases":1845,"url":28,"thumbnailPath":28,"statistic":1860,"gsStatistic":28,"type":55,"analyzePriority":28},[],{"issn":1806,"title":1807,"eissn":1808},{"VOID":877},{"EN":879},{"VOID":875},[1810,1814,1818,1822,1826,1830],{"id":909,"createTime":28,"updateTime":28,"relativeEntities":1811,"label":1812,"description":1813,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":912},{},{"id":885,"createTime":28,"updateTime":28,"relativeEntities":1815,"label":1816,"description":1817,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":888},{},{"id":891,"createTime":28,"updateTime":28,"relativeEntities":1819,"label":1820,"description":1821,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":894},{},{"id":897,"createTime":28,"updateTime":28,"relativeEntities":1823,"label":1824,"description":1825,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":900},{},{"id":903,"createTime":28,"updateTime":28,"relativeEntities":1827,"label":1828,"description":1829,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":906},{},{"id":915,"createTime":28,"updateTime":28,"relativeEntities":1831,"label":1832,"description":1833,"parentId":28,"standard":28,"scholarHubFieldId":28},[],{"EN":918},{},[1835,1840],{"id":922,"createTime":28,"updateTime":28,"relativeEntities":1836,"slug":28,"properties":1837,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1839,"statistic":28},[],{"title":1838},{"EN":926},[928],{"id":930,"createTime":28,"updateTime":28,"relativeEntities":1841,"slug":28,"properties":1842,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1844,"statistic":28},[],{"title":1843},{"EN":934},[],[1846,1853],{"id":938,"indexDatabase":1847,"url":950,"indexYears":28,"academicFieldIds":1852,"indexDatabaseRanking":28},{"id":940,"createTime":28,"updateTime":28,"relativeEntities":1848,"label":1849,"description":1850,"key":947,"publicationTags":1851,"standard":28},[],{"EN":943,"VI":943},{"EN":945,"VI":946},[949,813],[952],{"id":954,"indexDatabase":1854,"url":960,"indexYears":961,"academicFieldIds":1859,"indexDatabaseRanking":969},{"id":775,"createTime":28,"updateTime":28,"relativeEntities":1855,"label":1856,"description":1857,"key":781,"publicationTags":1858,"standard":28},[],{"EN":778,"VI":778},{"EN":778,"VI":780},[783],[963,964,965,966,967,968],{"impactFactor":32,"impactFactorByYear":1861,"i10Index":32,"i10IndexLast5Year":32,"totalPublication":972,"totalPublicationByYear":1862,"totalCitation":32,"totalCitationByYear":1863,"totalCitationPerPublication":32,"totalCitationPerPublicationByYear":1864,"hindexLast5Year":32,"hindex":32},{},{"2007":122,"2008":133,"2009":49,"2010":47,"2011":136,"2012":205,"2013":47,"2014":49,"2015":127,"2016":145,"2017":323,"2018":199,"2019":205,"2020":51,"2021":134,"2022":199,"2023":127,"2024":48},{},{},{"pages":1866,"volume":1868},{"VOID":1867},"225-244",{"VOID":1327},"2007-09-03",[949],{"id":1872,"createTime":1873,"updateTime":1874,"relativeEntities":1875,"slug":1876,"properties":1877,"entityType":995,"verifyStatus":26,"verifyTime":1874,"verifyNote":996,"languages":28,"translateLanguages":28,"viewCount":32,"primaryUrl":1886,"fullTextUrl":28,"authors":1887,"publicationType":1030,"publisherRelationship":1903,"citationCount":28,"citationInfo":28,"publishDate":1971,"publishYear":1742,"citationAnalyzeStatus":882,"lastCitationAnalyze":28,"indexDatabases":1972,"openAccess":28,"references":28,"isForceReanalyzing":1102},"06a71f37-d757-4e69-ace0-85b2bc393bb0","2024-01-13T21:43:42.056+00:00","2025-02-12T23:26:50.868+00:00",[],"Assessment-of-agricultural-sustainability-in-European-Union-countries-a-group-based-multivariate-trajectory-approach",{"abstract":1878,"title":1880,"references":1882,"doi":1884},{"EN":1879},"Sustainability of agriculture is difficult to measure and assess because it is a multidimensional concept that involves economic, social and environmental aspects and is subjected to temporal evolution and geographical differences. Existing studies assessing agricultural sustainability in the European Union (EU) are affected by several shortcomings that limit their relevance for policy makers. Specifically, most of them focus on farm level or cover a small set of countries, and the few exceptions covering a broad set of countries consider only a subset of the sustainable dimensions or rely on cross-sectional data. In this paper, we consider yearly data on 12 indicators (5 for the economic, 3 for the social and 4 for the environmental dimension) measured on 26 EU countries in the period 2004–2018 (15 years), and apply group-based multivariate trajectory modeling to identify groups of countries with common trends of sustainable objectives. An expectation-maximization algorithm is proposed to perform maximum likelihood estimation from incomplete data without relying on an explicit imputation procedure. Our results highlight three groups of countries with distinguished strong and weak sustainable objectives. Strong objectives common to all the three groups include improvement of productivity, increase of personal income in rural areas, reduction of poverty in rural areas, increase of production of renewable energy, rise of organic farming and reduction of nitrogen balance. Instead, enhancement of manager turnover and reduction of greenhouse gas emissions are weak objectives common to all the three groups of countries. Our findings represent a valuable resource to formulate new schemes for the attribution of subsidies within the Common Agricultural Policy (CAP).",{"EN":1881},"Assessment of agricultural sustainability in European Union countries: a group-based multivariate trajectory approach",{"VOID":1883},"Akaike, H.: A new look at the statistical model identification. IEEE Trans. Autom. Control 19(6), 716–723 (1974). https:\u002F\u002Fdoi.org\u002F10.1109\u002FTAC.1974.1100705\nAntle, J.M., Ray, S.: Sustainable Agricultural Development: An Economic Perspective. Palgrave Macmillan, Cham, CH (2020)\nBoker SM, Neale MC, Maes HH, Wilde MJ, Spiegel M, Brick TR, Estabrook R, Bates TC, Mehta P, von Oertzen T, Gore RJ, Hunter MD, Hackett DC, Karch J, Brandmaier A, Pritikin JN, Zahery M, Kirkpatrick RM (2018) Openmx user guide (release 2). https:\u002F\u002Fvipbg.vcu.edu\u002Fvipbg\u002FOpenMx2\u002Fdocs\u002F\u002FOpenMx\u002Flatest\u002FOpenMxUserGuide.pdf\nBozdogan, H.: Model selection and Akaike’s information criterion (AIC): The general theory and its analytical extensions. Psychometrika 52(3), 345–370 (1987). https:\u002F\u002Fdoi.org\u002F10.1007\u002FBF02294361\nCataldo R, Crocetta C, Grassia MG, Lauro NC, Marino M, Voytsekhovska V (2020) Methodological PLS-PM framework for SDGs system. Social Indicators Research published: 20 January 2020, https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11205-020-02271-5\nCristache, S.E., Vutǎ, M., Marin, E., Cioacǎ, S.I., Vutǎ, M.: Organic versus conventional farming: A paradigm for the sustainable development of the European countries. Sustainability 10, 4279 (2018). https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu10114279\nCzubak, W., Pawlowski, K.P.: Sustainable economic development of farms in central and Eastern European Countries driven by pro-investment mechanisms of the common agricultural policy. Agriculture 10, 93 (2020). https:\u002F\u002Fdoi.org\u002F10.3390\u002Fagriculture10040093\nCzyzewski, B., Matuszczak, A., Grzelak, A., Guth, M., Majchrzak, A.: Environmental sustainable value in agriculture revisited: How does Common Agricultural Policy contribute to eco-efficiency? Sustain. Sci. 43, 144–165 (2020). https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11625-020-00834-6\nDempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, Series B (Methodological) 39(1), 1–22 https:\u002F\u002Fdoi.org\u002F10.1111\u002Fj.2517-6161.1977.tb01600.x\nDennis, J.E., Mei, H.H.W.: Two new unconstrained optimization algorithms which use function and gradient values. J. Optim. Theory Appl. (1979). https:\u002F\u002Fdoi.org\u002F10.1007\u002FBF00932218\nDennis JE, Gay DM, Welsch RE (1981) An adaptive nonlinear least-squares algorithm. ACM Transactions on Mathematical Software https:\u002F\u002Fdoi.org\u002F10.1145\u002F355958.355965\nDraper, N.R., Smith, H.: Applied Regression Analysis, 2nd edn. Wiley, New York, US-NY (1981)\nEuropean Commission (2011) Horizon 2020: The framework programme for research and innovation. COM\u002F2011\u002F0808 final, 30th November 2011, Brussels, BE\nEuropean Commission (2020) The farm accountancy data network (FADN). https:\u002F\u002Fec.europa.eu\u002Fagriculture\u002Frica\u002Fdatabase\u002Fdatabase_en.cfm\nEuropean Commission (2020) Common monitoring and evaluation framework (CMEF) for the common agricultural policy (CAP) 2014-2020. https:\u002F\u002Fagridata.ec.europa.eu\u002Fextensions\u002FDataPortal\u002Fcmef_indicators.html\nEuropean Commission (2022) Eurostat database. https:\u002F\u002Fec.europa.eu\u002Feurostat\u002Fdata\u002Fdatabase\nFood and Agriculture Organization (2013) Sustainability assessment of food and agriculture systems: Indicators. FAO, Rome, IT. http:\u002F\u002Fwww.fao.org\u002Ffileadmin\u002Ftemplates\u002Fnr\u002Fsustainability_pathways\u002Fdocs\u002FSAFA_Indicators_final_19122013.pdf\nFood and Agriculture Organization (2014) Sustainability Assessment of Food and Agriculture Systems. Guidelines. FAO, Rome, IT. https:\u002F\u002Fwww.fao.org\u002F3\u002Fi3957e\u002Fi3957e.pdf\nFood and Agriculture Organization (FAO) (2022) FAOSTAT statistical database. https:\u002F\u002Fwww.fao.org\u002Ffaostat\u002Fen\u002F#home\nGaviglio, A., Bertocchi, M., Demartini, E.: A tool for the sustainability assessment of farms: Selection, adaptation and use of indicators for an Italian case study. Resources 6(4), 60 (2017). https:\u002F\u002Fdoi.org\u002F10.3390\u002Fresources6040060\nGennari, P., Navarro, D.K. (2019) The challenge of measuring agricultural sustainability in all its dimensions. Journal of Sustainable Research 1, e190013 https:\u002F\u002Fdoi.org\u002F10.20900\u002Fjsr20190013\nGiusti, A., Grassini, L.: Changes in tourist arrivals in Tuscan destinations between 2000 and 2013: A group based trajectory approach. Eur. J. Tour. Res. 14, 47–65 (2013)\nGómez-Limón, J.A., Sanchez-Fernandez, G.: Empirical evaluation of agricultural sustainability using composite indicators. Ecol. Econ. 69, 1062–1075 (2010). https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ecolecon.2009.11.027\nGursoy, D., Parroco, A.M., Scuderi, R.: An examination of tourism arrivals dynamics using short-term time series data: a space-time cluster approach. Tour. Econ. 19, 1–17 (2013). https:\u002F\u002Fdoi.org\u002F10.5367\u002Fte.2013.0318\nHannan, E.J., Quinn, B.G.: The determination of the order of an autoregression. Journal of the Royal Statistical Society. Ser. B (Methodol.) 41, 190–195 (1979). https:\u002F\u002Fdoi.org\u002F10.1111\u002FJ.2517-6161.1979.TB01072.X\nHayati, D., Ranjbar, Z., Karami, E.: Measuring agricultural sustainability. In: Lichtfouse, E. (ed.) Biodiversity, pp. 73–100. Biofuels, Agroforestry and Conservation Agriculture, Springer, Cham, CH (2010)\nHeggeseth, B.C., Jewell, N.P.: How Gaussian mixture models might miss detecting factors that impact growth patterns. Annal. Appl. Stat. 12(1), 222–245 (2018). https:\u002F\u002Fdoi.org\u002F10.1214\u002F17-AOAS1066\nJones, B.L., Nagin, D.S.: A note on a Stata plugin for estimating group-based trajectory models. Sociol. Methods Res. 42(4), 608–613 (2013). https:\u002F\u002Fdoi.org\u002F10.1177\u002F0049124113503141\nJones, B.L., Nagin, D.S., Roeder, K.: A SAS procedure based on mixture models for estimating developmental trajectories. Sociol. Methods Res. 29(3), 374–393 (2001). https:\u002F\u002Fdoi.org\u002F10.1177\u002F0049124101029003005\nL K Muthén and B O Muthén (2017) MPlus user’s guide. Muthén & Muthén, Los Angeles, US-CA, 8th edition\nLatruffe, L., Diazabakana, A., Bockstaller, C., Desjeux, Y., Finn, J., Kelly, E., Ryan, M., Uthes, S.: Measurement of sustainability in agriculture: A review of indicators. Stud. Agricul. Econ. 11(8), 123–130 (2016). https:\u002F\u002Fdoi.org\u002F10.7896\u002Fj.1624\nMagrini A (2022) gbmt: Group-Based Multivariate Trajectory Modeling. R package version 0.1.3. https:\u002F\u002Fcran.r-project.org\u002Fweb\u002Fpackages\u002Fgbmt\u002Findex.html\nMajewski, E.: Measuring and modelling farm level sustainability. Visegrad J. Bioecon. Sustain. Dev. 2(1), 2–10 (2013). https:\u002F\u002Fdoi.org\u002F10.2478\u002Fvjbsd-2013-0001\nMili, S., Martínez-Vega, J.: Accounting for regional heterogeneity of agricultural sustainability in Spain. Sustainability 11(2), 299 (2019). https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu11020299\nNagin, D.S.: Group-Based Modeling of Development. Harvard University Press, Cambridge, US-MA (2005)\nNagin, D.S., Jones, B.L., Passos, V.L., Tremblay, R.E.: Group-based multi-trajectory modeling. Stat. Methods Med. Res. 27(7), 2015–2023 (2018). https:\u002F\u002Fdoi.org\u002F10.1177\u002F0962280216673085\nNowak, A., Krukowski, A., Rózańska-Boczula, M.: Assessment of sustainability in agriculture of the European Union countries. Agronomy 9(12), 890 (2019). https:\u002F\u002Fdoi.org\u002F10.3390\u002Fagronomy9120890\nÖhlund, E., Zurek, K., Hammer, M.: Towards sustainable agriculture? The EU framework and local adaptation in Sweden and Poland. Environ. Policy Gov. 25, 270–287 (2015). https:\u002F\u002Fdoi.org\u002F10.1002\u002Feet.1687\nR Core Team (2020) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AT, https:\u002F\u002Fwww.R-project.org\nRadovanović, M., Lior, N.: Sustainable economic-environmental planning in Southeast Europe: Beyond GDP and climate change emphases. Irish J. Agricul. Food (2017). https:\u002F\u002Fdoi.org\u002F10.1002\u002Fsd.1679 published online\nRubin, D.B.: Inference and missing data. Biometrika 63(3), 581–592 (1976). https:\u002F\u002Fdoi.org\u002F10.2307\u002F2335739\nRubin, D.B.: Multiple imputation for nonresponse in surveys. Wiley, New York, US-NY (1987)\nRyan, M., Hennessy, T., Buckleya, C., Dillon, E.J., Donnellan, T., Hanrahan, K., Moran, B.: Developing farm-level sustainability indicators for Ireland using the Teagasc National Farm Survey. Irish J. Agricul. Food 55(2), 112–125 (2016). https:\u002F\u002Fdoi.org\u002F10.1515\u002Fijafr-2016-0011\nSchwarz, G.E.: Estimating the dimension of a model. Ann. Stat. 6(2), 461–464 (1978). https:\u002F\u002Fdoi.org\u002F10.1214\u002Faos\u002F1176344136\nSclove, S.L.: Application of model-selection criteria to some problems in multivariate analysis. Psychometrika 52(3), 333–343 (1987). https:\u002F\u002Fdoi.org\u002F10.1007\u002FBF02294360\nUN General Assembly (2015) Transforming our world: The 2030 Agenda for Sustainable Development. A\u002FRES\u002F70\u002F1. https:\u002F\u002Fsdgs.un.org\u002F2030agenda\nVan der Nest, G., Lima Passos, V., Candel, M.J.J.M., Van Breukelen, G.J.P.: An overview of mixture modelling for latent evolutions in longitudinal data: Modelling approaches, fit statistics and software. Advances in Life Course Research 43, (2020). https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.alcr.2019.100323\nWECD: Our Common Future: Report of the World Commission on Environment and Development, transmitted to the General Assembly as an Annex to document A\u002F42\u002F427 - Development and International Cooperation: Environment. United Nations, Geneva, CH (1987). https:\u002F\u002Fsustainabledevelopment.un.org\u002Fcontent\u002Fdocuments\u002F5987our-common-future.pdf",{"VOID":1885},"10.1007\u002Fs10182-022-00437-9","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10182-022-00437-9",[1888],{"id":1889,"sortIndex":32,"researcher":28,"roles":1890,"affiliations":1891,"properties":1900,"displayName":1902,"givenName":28,"familyName":28},"e0dea066-c8c2-4a73-abb2-14689f7b1061",[1002],[1892],{"id":1893,"sortIndex":32,"affiliation":1894,"properties":28},"73721c05-b231-4034-881c-a157bb18b3c7",{"id":1893,"createTime":28,"updateTime":28,"relativeEntities":1895,"slug":28,"properties":1896,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":1899,"statistic":28},[],{"title":1897},{"VI":1898},"Department of Statistics, Computer Science, Applications, University of Florence, Florence, 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article considers a modeling problem of integer-valued time series of bounded counts in which the binomial index of dispersion of the observations is greater than one, i.e., the observations inhere the characteristic of extra-binomial variation. Most methods analyzing such characteristic are based on the conditional mean process instead of the observed process itself. To fill this gap, we introduce a new class of beta-binomial integer-valued GARCH models, establish the geometric moment contracting property of its conditional mean process, discuss the stationarity and ergodicity of the observed process and its conditional mean process, and give some stochastic properties of them. We consider the conditional maximum likelihood estimates and establish the asymptotic properties of the estimators. The performances of these estimators are compared via simulation studies. Finally, we apply the proposed models to two real data sets.",{"EN":1983},"A new class of integer-valued GARCH models for time series of bounded counts with extra-binomial variation",{"VOID":1985},"Agosto, A., Cavaliere, G., Kristensen, D., Rahbek, A.: Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX). J. Empir. 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Time Series Anal. 35, 115–132 (2014)\nWeiß, C.H., Testik, M.C.: On the Phase I analysis for monitoring time-dependent count processes. IIE Trans. 47, 294–306 (2015)\nWilliams, D.: The analysis of binary responses from toxicological experiments involving reproduction and teratogenicity. Biometrics 31, 949–952 (1975)\nWintenberger, O.: Continuous invertibility and stable QML estimation of the EGARCH(1,1) model. Scan. J. Stat. 40, 846–867 (2013)\nWu, W., Shao, X.: Limit theorems for iterated random functions. J. Appl. Prob. 41, 425–436 (2004)\nZhu, F., Shi, L., Liu, S.: Influence diagnostics in log-linear integer-valued GARCH models. Adv. Stat. Anal. 99, 311–335 (2015)\nZhu, F., Liu, S., Shi, L.: Local influence analysis for Poisson autoregression with an application to stock transaction data. Stat. Neerlandica 70, 4–25 (2016)",{"VOID":1987},"10.1007\u002Fs10182-021-00414-8","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs10182-021-00414-8",[1990,2005,2020],{"id":1991,"sortIndex":32,"researcher":28,"roles":1992,"affiliations":1993,"properties":2002,"displayName":2004,"givenName":28,"familyName":28},"5bdd7d41-47dc-4fad-9a35-be3c51f31ef1",[1002],[1994],{"id":1995,"sortIndex":32,"affiliation":1996,"properties":28},"4f6c4145-179a-4f8f-9238-6b3aa36b307b",{"id":1995,"createTime":28,"updateTime":28,"relativeEntities":1997,"slug":28,"properties":1998,"entityType":28,"verifyStatus":28,"verifyTime":28,"verifyNote":28,"languages":28,"translateLanguages":28,"viewCount":28,"url":28,"parentIds":2001,"statistic":28},[],{"title":1999},{"EN":2000},"School of Mathematics and Statistics, Henan University, Kaifeng, China",[],{"title":2003},{"VI":2004},"Huaping 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Uncertainty Fuzziness Knowledge-Based Syst. 10(5), 477–491 (2002)\nDomingo-Ferrer, J., Torra, V.: A quantitative comparison of disclosure control methods for microdata. In: Doyle, P., Lane, J., Theeuwes, J., Zayatz, L. (eds.) Confidentiality, Disclosure, and Data Access, pp. 111–133. North-Holland, Amsterdam (2001)\nFritsch, M., Stephan, A.: Die Heterogenität der technischen Effizienz innerhalb von Wirtschaftszweigen—Auswertungen auf Grundlage der Kostenstrukturstatistik des Statistischen Bundesamtes. In: Pohl, R., Fischer, J., Rockmann, U., Semlinger, K. (eds.) Analysen zur regionalen Industrieentwicklung—Sonderauswertungen einzelbetrieblicher Daten der amtlichen Statistik, pp. 143–156. Statistisches Landesamt, Berlin (2003)\nHastie, T., Tibshirani, R.: Generalized Additive Models. Chapman & Hall, London (1990)\nRonning, G., Sturm, R., Höhne, J., Lenz, R., Rosemann, M., Scheffler, M., Vorgrimler, D.: Handbuch zur Anonymisierung wirtschaftsstatistischer Mikrodaten. Statistik und Wissenschaft, vol. 4. Statistisches Bundesamt, Wiesbaden (2005)\nRosemann, M.: Erste Ergebnisse von vergleichenden Untersuchungen mit anonymisierten und nicht anonymisierten Einzeldaten am Beispiel der Kostenstrukturerhebung und der Umsatzsteuerstatistik. In: Ronning, G., Gnoss, R. (eds.) Anonymisierung wirtschaftsstatistischer Einzeldaten. Forum der Bundesstatistik, vol. 42, pp. 154–183. Statistisches Bundesamt, Wiesbaden (2003)\nSchmid, M.: Estimation of a linear model under microaggregation by individual ranking. Allgemeines Stat. Arch. 90(3), 419–438 (2006)\nSchmid, M., Schneeweiss, H.: The effect of microaggregation procedures on the estimation of linear models: A simulation study. In: Pohlmeier, W., Ronning, G., Wagner, J. (eds.) Econometrics of Anonymized Micro Data. Jahrbücher für Nationalökonomie und Statistik, vol. 225(5), pp. 529–543. Lucius & Lucius, Stuttgart (2005)\nSchmid, M., Schneeweiss, H., Küchenhoff, H.: Estimation of a linear regression under microaggregation with the response variable as a sorting variable. Stat. Neerlandica 61(4), 407–431 (2007)\nWillenborg, L., de Waal, T.: Elements of Statistical Disclosure Control. Springer, New York (2001)\nWinkler, W.E.: Single-ranking micro-aggregation and reidentification. 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