The Muscatine children's obesity data reanalysed using pattern mixture models

被引：36

作者：

Ekholm, A

Skinner, C

机构：

[1] Univ Helsinki, Dept Stat, FIN-00014 Helsinki, Finland

[2] Univ Southampton, Southampton, Hants, England

来源：

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS | 1998年 / 47卷

关键词：

cohort data; correlated binary data; dependence ratio; informative non-response; selection model;

D O I：

10.1111/1467-9876.00110

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

A set of longitudinal binary, partially incomplete, data on obesity among children in the USA is reanalysed. The multivariate Bernoulli distribution is parameterized by the univariate marginal probabilities and dependence ratios of all orders, which together support maximum likelihood inference. The temporal association of obesity is strong and complex but stationary. We fit a saturated model for the distribution of response patterns and find that non-response is completely at random for boys but that the probability of obesity is consistently higher among girls who provided incomplete records than among girls who provided complete records. We discuss the statistical and substantive features of respectively pattern mixture and selection models for this data set.

引用

页码：251 / 263

页数：13

共 17 条

[1]

AZZALINI A, 1994, BIOMETRIKA, V81, P767

[2] MARGINAL REGRESSION FOR REPEATED BINARY DATA WITH OUTCOME SUBJECT TO NON-IGNORABLE NONRESPONSE [J].