Minimum phi-divergence estimators for multinomial logistic regression with complex sample design

作者：Castilla Elena; Martin Nirian; Pardo Leandro^*

来源：ASTA-Advances in Statistical Analysis, 2018, 102(3): 381-411.

DOI：10.1007/s10182-017-0311-6

• Design effect
• Cluster sampling
• Pseudo-likelihood
• Sample weight

This article develops the theoretical framework needed to study the multinomial regression model for complex sample design with pseudo-minimum phi-divergence estimators. The numerical example and the simulation study propose new estimators for the parameter of the logistic regression with overdispersed multinomial distributions for the response variables, the pseudo-minimum Cressie-Read divergence estimators, as well as new estimators for the intra-cluster correlation coefficient. The simulation study shows that the Binder's method for the intra-cluster correlation coefficient exhibits an excellent performance when the pseudo-minimum Cressie-Read divergence estimator, with , is plugged.

• 出版日期2018-7