Biometrics
0006-341X
1541-0420
Anh Quốc
Cơ quản chủ quản: WILEY , Wiley-Blackwell Publishing Ltd
Lĩnh vực:
Statistics and ProbabilityMedicine (miscellaneous)Applied MathematicsBiochemistry, Genetics and Molecular Biology (miscellaneous)Immunology and Microbiology (miscellaneous)Agricultural and Biological Sciences (miscellaneous)
Các bài báo tiêu biểu
Estimation of the Proportional Hazard in Two-Treatment-Group Clinical Trials
Tập 37 Số 3 - Trang 513 - 1981
Modifying the t Test for Assessing the Correlation Between Two Spatial Processes
Tập 49 Số 1 - Trang 305 - 1993
Bayesian Approaches to Modeling the Conditional Dependence Between Multiple Diagnostic Tests Summary. Many analyses of results from multiple diagnostic tests assume the tests are statistically independent conditional on the true disease status of the subject. This assumption may be violated in practice, especially in situations where none of the tests is a perfectly accurate gold standard. Classical inference for models accounting for the conditional dependence between tests requires that results from at least four different tests be used in order to obtain an identifiable solution, but it is not always feasible to have results from this many tests. We use a Bayesian approach to draw inferences about the disease prevalence and test properties while adjusting for the possibility of conditional dependence between tests, particularly when we have only two tests. We propose both fixed and random effects models. Since with fewer than four tests the problem is nonidentifiable, the posterior distributions are strongly dependent on the prior information about the test properties and the disease prevalence, even with large sample sizes. If the degree of correlation between the tests is known a priori with high precision, then our methods adjust for the dependence between the tests. Otherwise, our methods provide adjusted inferences that incorporate all of the uncertainty inherent in the problem, typically resulting in wider interval estimates. We illustrate our methods using data from a study on the prevalence of Strongyloides infection among Cambodian refugees to Canada.
Tập 57 Số 1 - Trang 158-167 - 2001
Hierarchical Bayesian Modeling of Spatially Correlated Health Service Outcome and Utilization Rates Summary Neal, 1995 ,Bayesian Learning for Neural Networks; Gustafson, MacNab, and Wen, 2003 ,Statistics and Computing, to appear) is used for posterior sampling of the random effects. To illustrate relevant problems, methods, and techniques, we present an analysis of regional variation in intraventricular hemorrhage incidence rates among neonatal intensive care unit patients across Canada.
Tập 59 Số 2 - Trang 305-315 - 2003
A Score Test for Testing a Zero‐Inflated Poisson Regression Model Against Zero‐Inflated Negative Binomial Alternatives Summary. Count data often show a higher incidence of zero counts than would be expected if the data were Poisson distributed. Zero‐inflated Poisson regression models are a useful class of models for such data, but parameter estimates may be seriously biased if the nonzero counts are overdispersed in relation to the Poisson distribution. We therefore provide a score test for testing zero‐inflated Poisson regression models against zero‐inflated negative binomial alternatives.
Tập 57 Số 1 - Trang 219-223 - 2001