MMI: Multimodel inference or models with management implications?

Journal of Wildlife Management - Tập 79 Số 5 - Trang 708-718 - 2015
John Fieberg1, Douglas H. Johnson2
1Department of Fisheries, Wildlife, and Conservation Biology, University of Minnesota, 2003 Upper Buford Circle, Suite 135, Saint Paul, MN 55108, USA
2U.S. Geological Survey; Northern Prairie Wildlife Research Center; 2003 Upper Buford Circle; Suite 135, Saint Paul MN 55108 USA

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Tài liệu tham khảo

Altman, 1989, Bootstrap investigation of the stability of a Cox regression model, Statistics in Medicine, 8, 771, 10.1002/sim.4780080702

Babyak, 2004, What you see may not be what you get: a brief, nontechnical introduction to overfitting in regression-type models, Psychosomatic Medicine, 66, 411

Box, 1966, Use and abuse of regression, Technometrics, 8, 625, 10.2307/1266635

Breiman, 1992, The little bootstrap and other methods for dimensionality selection in regression: X-fixed prediction error, Journal of the American Statistical Association, 87, 738, 10.1080/01621459.1992.10475276

Buckland, 1997, Model selection: an integral part of inference, Biometrics, 53, 603, 10.2307/2533961

Burnham, 1998, Model selection and inference: a practical information-theoretic approach. First edition, 10.1007/978-1-4757-2917-7

Burnham, 2002, Model selection and multimodel inference: a practical information-theoretic approach. Second edition

Burnham, 2004, Multimodel inference understanding AIC and BIC in model selection, Sociological Methods and Research, 33, 261, 10.1177/0049124104268644

Cade, 2015, Model averaging and muddled multimodel inferences, Ecology, 96, 10.1890/14-1639.1

Chamberlin, 1890, The method of multiple working hypotheses, Science, 15, 92, 10.1126/science.ns-15.366.92

Chatfield, 1995, Model uncertainty, data mining and statistical inference, Journal of the Royal Statistical Society, Series A, 158, 419, 10.2307/2983440

Claeskens, 2007, An asymptotic theory for model selection inference in general semiparametric problems, Biometrika, 94, 249, 10.1093/biomet/asm034

Commoner, 1971, The closing circle. Alfred

Copas, 1997, Using regression models for prediction: shrinkage and regression to the mean, Statistical Methods in Medical Research, 6, 167, 10.1177/096228029700600206

Copas, 1991, Estimating the residual variance in orthogonal regression with variable selection, Statistician, 40, 51, 10.2307/2348223

Dahlgren, 2010, Alternative regression methods are not considered in Murtaugh (2009) or by ecologists in general, Ecology Letters, 13.5, E7, 10.1111/j.1461-0248.2010.01460.x

Dormann, 2013, Collinearity: a review of methods to deal with it and a simulation study evaluating their performance, Ecography, 36, 027, 10.1111/j.1600-0587.2012.07348.x

Draper, 1995, Assessment and propagation of model uncertainty (with discussion), Journal of the Royal Statistical Society, Series B, 57, 45, 10.1111/j.2517-6161.1995.tb02015.x

Eberhardt, 2003, What should we do about hypothesis testing?, Journal of Wildlife Management, 67, 241, 10.2307/3802765

Faraway, 1992, On the cost of data analysis, Journal of Computational and Statistical Graphics, 1, 213, 10.1080/10618600.1992.10474582

Fieberg, 2012, Understanding the causes and consequences of animal movement: a cautionary note on fitting and interpreting regression models with time-dependent covariates, Methods in Ecology and Evolution, 3, 983, 10.1111/j.2041-210X.2012.00239.x

Foster, 2006, Honest confidence intervals for the error variance in stepwise regression, Journal of Economic and Social Measurement, 31, 89, 10.3233/JEM-2006-02266

Fox, 2003, Effect displays in R for generalized linear models, Journal of Statistical Software, 8, 1, 10.18637/jss.v008.i15

Galipaud, 2014, Ecologists overestimate the importance of predictor variables in model averaging: a plea for cautious interpretations, Methods in Ecology and Evolution, 5, 983, 10.1111/2041-210X.12251

Gelman, 2007, Data analysis using regression and multilevel/hierarchical models

Giudice, 2012, Spending degrees of freedom in a poor economy: a case study of building a sightability model for moose in northeastern Minnesota, Journal of Wildlife Management, 76, 75, 10.1002/jwmg.213

Graham, 2003, Confronting multicollinearity in ecological multiple regression, Ecology, 84, 2809, 10.1890/02-3114

Harrell, 2001, Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis, 10.1007/978-1-4757-3462-1

Hegyi, 2011, Using information theory as a substitute for stepwise regression in ecology and behavior, Behavioral Ecology and Sociobiology, 65, 69, 10.1007/s00265-010-1036-7

Hernán, 2011, The Simpson's paradox unraveled, International Journal of Epidemiology, 40, 780, 10.1093/ije/dyr041

Hernán, 2002, Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiology, American Journal of Epidemiology, 155, 176, 10.1093/aje/155.2.176

Hjort, 2003, Frequentist model average estimators, Journal of the American Statistical Association, 98, 879, 10.1198/016214503000000828

Hoeting, 1999, Bayesian model averaging: a tutorial, Statistical Science, 14, 382

Hooten, 2015, A guide to Bayesian model selection for ecologists, Ecological Monographs, 85, 3, 10.1890/14-0661.1

Jensen, 2015, Simultaneous inference for model averaging of derived parameters, Risk Analysis, 35, 68, 10.1111/risa.12242

Johnson, 2002, The importance of replication in wildlife research, Journal of Wildlife Management, 66, 919, 10.2307/3802926

2014

Kaplan , D. T. 2009

Kutner, 2005, Applied linear models, 5

Lukacs, 2010, Model selection bias and Freedman's paradox, Annals of the Institute of Statistical Mathematics, 62, 117, 10.1007/s10463-009-0234-4

Mundry, 2009, Stepwise model fitting and statistical inference: turning noise into signal pollution, American Naturalist, 173, 119, 10.1086/593303

Murray, 2009, Methods to quantify variable importance: implications for the analysis of noisy ecological data, Ecology, 90, 348, 10.1890/07-1929.1

Murtaugh, 1998, Methods of variable selection in regression modeling, Communications in Statistics - Simulation and Computation, 27, 711, 10.1080/03610919808813505

Murtaugh, 2009, Performance of several variable-selection methods applied to real ecological data, Ecology Letters, 12, 1061, 10.1111/j.1461-0248.2009.01361.x

Murtaugh, 2014, In defense of P values, Ecology, 95, 611, 10.1890/13-0590.1

Pearl, 2000, Causality: models, reasoning, and inference

Pearl , J. 2012 in

Pugesek, 2003, Structural equation modeling: applications in ecological and evolutionary biology, 10.1017/CBO9780511542138

Raftery, 2003, Discussion: performance of Bayesian model averaging, Journal of the American Statistical Association, 98, 931, 10.1198/016214503000000891

Robel, 1970, Relationships between visual obstruction measurements and weight of grassland vegetation, Journal of Range Management, 23, 295, 10.2307/3896225

Schildcrout, 2011, Analyses of longitudinal, hospital clinical laboratory data with application to blood glucose concentrations, Statistics in Medicine, 30, 3208, 10.1002/sim.4352

Shipley , B. 2002

Turek, 2012, Model-averaged Wald confidence intervals, Computational Statistics and Data Analysis, 56, 2809, 10.1016/j.csda.2012.03.002

van Houwelingen, 2001, Shrinkage and penalized likelihood as methods to improve predictive accuracy, Statistica Neerlandica, 55, 17, 10.1111/1467-9574.00154

Wang, 2013, Interval estimation by frequentist model averaging, Communications in Statistics-Theory and Methods, 42, 4342, 10.1080/03610926.2011.647218

Whittingham, 2006, Why do we still use stepwise modelling in ecology and behaviour?, Journal of Animal Ecology, 75, 1182, 10.1111/j.1365-2656.2006.01141.x

Yu, 2014, Transformation-based model averaged tail area inference, Computational Statistics, 29, 1713, 10.1007/s00180-014-0514-1

Zicus, 2003, Does mallard clutch size vary with landscape composition: a different view, Wilson Bulletin, 114, 409, 10.1676/03-064