Abstract

The purpose of this proposal is to develop diagnostics and graphics for repeated measures data fit using random effects models. There are three complementary parts, i.) to develop methods for outlier detection and residual analysis, ii.) to develop methods to detect influential observations and influential assumptions, and iii.) to develop graphical methods for inspecting repeated measures data in the context of a random effects model.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
First Independent Research Support & Transition (FIRST) Awards (R29)
Project #
5R29GM050011-02
Application #
2187587
Study Section
Special Emphasis Panel (ZRG7-SSS-1 (05))
Project Start
1993-08-01
Project End
1998-07-31
Budget Start
1994-08-01
Budget End
1995-07-31
Support Year
2
Fiscal Year
1994
Total Cost
Indirect Cost

  Institution

Name
University of California Los Angeles
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
119132785
City
Los Angeles
State
CA
Country
United States
Zip Code
90095

  Publications

Taylor, J M; Weiss, R E; Li, W et al. (2001) Estimation for paired binomial data with application to radiation therapy. Stat Med 20:3375-90
Weiss, R E; Cho, M; Yanuzzi, M (1999) On Bayesian calculations for mixture likelihoods and priors. Stat Med 18:1555-70
Weiss, R E; Wang, Y; Ibrahim, J G (1997) Predictive model selection for repeated measures random effects models using Bayes factors. Biometrics 53:592-602