DESCRIPTION: This application proposes extension of the investigator's
previous work on the analysis of longitudinal studies arising in cancer
research. The approach is concerned with both randomized clinical trials
and epidemiological investigations. In particular, the applicant proposes
to address the issue of adjusting for confounders that are observed
post-randomization in randomized clinical trials. The applicant has
previously postulated the view that since the confounder is observed
post-randomization, it should be treated as an outcome variable and analyzed
accordingly, rather than regarded as a covariate or predictor value.
This approach will be extended in the proposed work with the following
specific goals: 1) Developing methods for adjusting for survival
confounding measures in repeated measures analysis. 2) Developing methods
to deal with informative censoring in non-ignorable non-response in
longitudinal trials. 3) Conduct a simulation study of the conditional
inference procedures of the methodology. 4)Develop procedures for analyzing
bivariate repeated measures data. 5)Develop procedures for performing
sample size calculations for repeated measures with both discrete and
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