Comput Methods Programs Biomed - A warning concerning the estimation of multinomial logistic models with correlated responses in SAS.

Tópicos

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Resumo

Kuss and McLerran in a paper in this journal provide SAS code for the estimation of multinomial logistic models for correlated data. Their motivation derived from two papers that recommended to estimate such models using a Poisson likelihood, which is according to Kuss and McLerran "statistically correct but computationally inefficient". Kuss and McLerran propose several estimating methods. Some of these are based on the fact that the multinomial model is a multivariate binary model. Subsequently a procedure proposed by Wright is exploited to fit the models. In this paper we will show that the new computation methods, based on the approach by Wright, are statistically incorrect because they do not take into account that for multinomial data a multivariate link function is needed. An alternative estimation strategy is proposed using the clustered bootstrap.

Resumo Limpo

kuss mclerran paper journal provid sas code estim multinomi logist model correl data motiv deriv two paper recommend estim model use poisson likelihood accord kuss mclerran statist correct comput ineffici kuss mclerran propos sever estim method base fact multinomi model multivari binari model subsequ procedur propos wright exploit fit model paper will show new comput method base approach wright statist incorrect take account multinomi data multivari link function need altern estim strategi propos use cluster bootstrap

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