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作者：Holland, B; Cheung, SH
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University; Chinese University of Hong Kong
摘要：A criticism of multiple-comparison procedures is that the family of inferences over which an error rate is controlled is often arbitrarily selected, yet the conclusion may depend heavily on the choice of the family. Such ambiguity is most likely in large exploratory studies requiring numerous simultaneous inferences. In ambiguous situations it is desirable that results of multiple-comparison procedures depend little on the chosen family. To assess this, we propose several familywise robustness...
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作者：Casella, G; Mengersen, KL; Robert, CP; Titterington, DM
作者单位：Universite PSL; Universite Paris-Dauphine; State University System of Florida; University of Florida; Queensland University of Technology (QUT); Institut Polytechnique de Paris; ENSAE Paris; University of Glasgow
摘要：We consider the construction of perfect samplers for posterior distributions associated with mixtures of exponential families and conjugate priors, starting with a perfect slice sampler in the spirit of Mira and co-workers. The methods rely on a marginalization akin to Rao-Blackwellization and illustrate the duality principle of Diebolt and Robert. A first approximation embeds the finite support distribution on the latent variables within a continuous support distribution that is easier to sim...
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作者：Kent, JT; Bowman, A; Velilla, S; Zhang, WY; Critchley, F; Atkinson, A; Yao, QW; Welsh, AH; Cui, HJ; Li, GY; Spokoiny, V; Chan, KS; Li, MC; Cízek, P; Härdle, W; Yang, LJ; Cook, RD; Fan, JQ; Ferré, L; Li, KC; Li, LX; Linton, O; Ni, LQ; Ohtaki, M; Fujikoshi, Y; Schoff, JR; Setodji, CM; Stenseth, NC; Lingjærde, OC
作者单位：University of Leeds; University of Glasgow; Universidad Carlos III de Madrid; University of London; London School Economics & Political Science; University of Southampton; Beijing Normal University; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Leibniz Association; Weierstrass Institute for Applied Analysis & Stochastics; Humboldt University of Berlin; University of Iowa; Emmes Corporation; Michigan State University; University of Minnesota System; University of Minnesota Twin Cities; University of North Carolina; University of North Carolina Chapel Hill; Universite de Toulouse; Universite Toulouse 1 Capitole; University of California System; University of California Los Angeles; Hiroshima University; State University System of Florida; University of Central Florida; University of Oslo
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作者：Yau, KKW; Kuk, AYC
作者单位：City University of Hong Kong; National University of Singapore
摘要：Generalized linear mixed models (GLMMs) are widely used to analyse non-normal response data with extra-variation, but non-robust estimators are still routinely used. We propose robust methods for maximum quasi-likelihood and residual maximum quasi-likelihood estimation to limit the influence of outlying observations in GLMMs. The estimation procedure parallels the development of robust estimation methods in linear mixed models, but with adjustments in the dependent variable and the variance co...
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作者：Brooks, SP
作者单位：University of Cambridge; University of Warwick; Aalto University; University of London; University College London; Universite PSL; Universite Paris-Dauphine; University of Glasgow; Imperial College London; University of Aberdeen; University of Valencia; University of Southampton; University of Bristol; University of Oxford; University of California System; University of California Santa Cruz; Duke University; University of Trieste; University of Minnesota System; University of Minnesota Twin Cities; Seoul National University (SNU); Umea University; Harvard University; University of Chicago
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作者：Balding, DJ; Carothers, AD; Marchini, JL; Cardon, LR; Vetta, A; Griffiths, B; Weir, BS; Hill, WG; Goldstein, D; Strimmer, K; Myers, S; Beaumont, MA; Glasbey, CA; Mayer, CD; Richardson, S; Marshall, C; Durrett, R; Nielsen, R; Visscher, PM; Knott, SA; Haley, CS; Ball, RD; Hackett, CA; Holmes, S; Husmeier, D; Jansen, RC; ter Braak, CJF; Maliepaard, CA; Boer, MP; Joyce, P; Li, N; Stephens, M; Marcoulides, GA; Drezner, Z; Mardia, K; McVean, G; Meng, XL; Ochs, MF; Pagel, M; Sha, N; Vannucci, M; Sillanpää, MJ; Sisson, S; Yandell, BS; Jin, CF; Satagopan, JM; Gaffney, PJ; Zeng, ZB; Broman, KW; Speed, TP; Fearnhead, P; Donnelly, P; Larget, B; Simon, DL; Kadane, JB; Nicholson, G; Smith, AV; Jónsson, F; Gústafsson, O; Stefánsson, K; Donnelly, P; Parmigiani, G; Garrett, ES; Anbazhagan, R; Gabrielson, E
作者单位：Imperial College London; University of Edinburgh; University of Oxford; North Carolina State University; University of Edinburgh; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; University of Munich; University of Reading; James Hutton Institute; Cornell University; UK Research & Innovation (UKRI); Biotechnology and Biological Sciences Research Council (BBSRC); Roslin Institute; Scion; James Hutton Institute; Stanford University; University of Groningen; University of Idaho; University of Washington; University of Washington Seattle; California State University System; California State University Fullerton; University of Leeds; University of Chicago; Fox Chase Cancer Center; Texas A&M University System; Texas A&M University College Station; University of Puerto Rico; University of Wisconsin System; University of Wisconsin Madison; North Carolina State University
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作者：Shi, JQ; Copas, J
作者单位：University of Warwick; University of Glasgow
摘要：A major difficulty in meta-analysis is publication bias. Studies with positive outcomes are more likely to be published than studies reporting negative or inconclusive results. Correcting for this bias is not possible without making untestable assumptions. In this paper, a sensitivity analysis is discussed for the meta-analysis of 2x2 tables using exact conditional distributions. A Markov chain Monte Carlo EM algorithm is used to calculate maximum likelihood estimates. A rule for increasing th...
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作者：Ollila, E; Oja, H; Hettmansperger, TP
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：A new estimator of the regression parameters is introduced in a multivariate multiple-regression model in which both the vector of explanatory variables and the vector of response variables are assumed to be random. The affine equivariant estimate matrix is constructed using the sign covariance matrix (SCM) where the sign concept is based on Oja's criterion function. The influence function and asymptotic theory are developed to consider robustness and limiting efficiencies of the SCM regressio...
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作者：Lauritzen, SL; Richardson, TS
作者单位：Aalborg University; University of Washington; University of Washington Seattle
摘要：Chain graphs are a natural generalization of directed acyclic graphs and undirected graphs. However, the apparent simplicity of chain graphs belies the subtlety of the conditional independence hypotheses that they represent. There are many simple and apparently plausible, but ultimately fallacious, interpretations of chain graphs that are often invoked, implicitly or explicitly. These interpretations also lead to flawed methods for applying background knowledge to model selection. We present a...
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作者：Dawid, AP; Cox, DR; Kreiner, S; Green, P; Shipley, B; Kent, JT; Smith, JQ; Koster, JTA; Madigan, D; Andersson, SA; Perlman, MD; Robert, CP; Marin, JM; Rosenbaum, PR; Roverato, A; Consonni, G; Studeny, M
作者单位：University of London; University College London; University of Oxford; University of Copenhagen; University of Bristol; University of Sherbrooke; University of Leeds; University of Warwick; Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC; Rutgers University System; Rutgers University New Brunswick; Indiana University System; Indiana University Bloomington; University of Washington; University of Washington Seattle; Universite PSL; Universite Paris-Dauphine; University of Pennsylvania; Universita di Modena e Reggio Emilia; University of Pavia; Czech Academy of Sciences
