Analysis of ordinal outcomes with longitudinal covariates subject to missingness

Abstract

We propose a mixture model for data with an ordinal outcome and a longitudinal covariate that is subject to missingness. Data from a tailored telephone delivered, smoking cessation intervention for construction laborers are used to illustrate the method, which considers as an outcome a categorical measure of smoking cessation, and evaluates the effectiveness of the motivational telephone interviews on this outcome. We propose two model structures for the longitudinal covariate, for the case when the missing data are missing at random, and when the missing data mechanism is non-ignorable. A generalized EM algorithm is used to obtain maximum likelihood estimates.

Keywords:

• ordinal outcomes
• longitudinal covariates
• missingness

Acknowledgements

The research of Dr Goodman was supported by National Institute of Child Health and Human Development grant 5 F31 HD043695, National Cancer Institute grant U54CA153460, the Barnes-Jewish Hospital Foundation, Sitmeman Cancer Center, and Washington University School of Medicine. The research of Dr Li was supported by National Institute of Health grant R01CA95747.