Title
A pairwise likelihood approach for longitudinal data with missing observations in both response and covariates.
Abstract
Missing observations occur commonly in longitudinal studies, and it has been documented that biased results could arise if such a feature is not properly accounted for in the analysis. A large body of methods handle missingness arising either from response components or covariate variables, but relatively little attention has been directed to addressing missingness in both response and covariate variables simultaneously. The sparsity of the research on this topic is partially attributed to substantially increased complexity of modeling and computational difficulty. In particular, the likelihood method may become infeasible in handling high dimensional data. This paper explores pairwise likelihood methods to handle longitudinal data with missing observations in both response and covariate variables. A unified framework based on bivariate normal distributions is invoked to accommodate various types of missing data patterns, including non-ignorable and non-monotone missingness. The performance of the proposed methods is assessed under a variety of circumstances. In particular, issues on efficiency and robustness are investigated. Longitudinal survey data from the Waterloo Smoking Prevention Project are analyzed with the proposed methods.
Year
DOI
Venue
2013
10.1016/j.csda.2013.06.001
Computational Statistics & Data Analysis
Keywords
Field
DocType
longitudinal data,longitudinal study,covariate variable,pairwise likelihood approach,missing data pattern,missing observation,response component,non-monotone missingness,high dimensional data,longitudinal survey data
Econometrics,Prevention project,Survey data collection,Pairwise comparison,Clustering high-dimensional data,Covariate,Computer science,Robustness (computer science),Multivariate normal distribution,Missing data,Statistics
Journal
Volume
Issue
ISSN
68
C
0167-9473
Citations 
PageRank 
References 
3
0.78
3
Authors
2
Name
Order
Citations
PageRank
Haocheng Li1636.47
Grace Y. Yi263.78