The primary goal of our project is to develop and evaluate statistical methods for neurological studies. The secondary goal is to disseminate these methods by writing computer programs, specifically SAS Macros. The statistical problems to be investigated in this proposal arise from the NIH-funded projects in which the Principal Investigator has been participating. Although these problems have frequently arisen in other fields as well, satisfactory solutions have not, as of yet, been found.
Specific Aim 1 is to develop methods for the Cox proportional hazards model when covariates are partially missing. Specifically, we propose to develop a likelihood-based imputation method with or without specifying functional form of the distribution for missing covariate under various missing mechanisms.
Specific Aim 2 is to develop methods for handling missing data in repeated measures analysis under various missing mechanisms.
Specific Aim 3 is to develop a joint estimating equation method for handling nonignorably missing outcomes in bivariate binary data arising from Northern Manhattan Stroke Study.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS036928-03
Application #
6393600
Study Section
Special Emphasis Panel (ZRG1-STA (01))
Program Officer
Gilbert, Peter R
Project Start
1999-07-01
Project End
2002-06-30
Budget Start
2001-07-01
Budget End
2002-06-30
Support Year
3
Fiscal Year
2001
Total Cost
$91,106
Indirect Cost
Name
Columbia University (N.Y.)
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
167204994
City
New York
State
NY
Country
United States
Zip Code
10032
Lee, Hye-Seung; Cho Paik, Myunghee; Lee, Joseph H (2009) Estimating a multivariate familial correlation using joint models for canonical correlations: application to memory score analysis from familial Hispanic Alzheimer's disease study. Biometrics 65:463-9
Paik, Myunghee Cho; Wang, Cuiling (2009) HANDLING MISSING DATA BY DELETING COMPLETELY OBSERVED RECORDS. J Stat Plan Inference 139:2341-2350
Lee, Hye-Seung; Paik, Myunghee Cho; Lee, Joseph H (2008) Genotype-adjusted familial correlation analysis using three generalized estimating equations. Stat Med 27:5471-83
Cho Paik, Myunghee (2004) Nonignorable missingness in matched case-control data analyses. Biometrics 60:306-14
Lin, I F; Paik, M C (2001) Matched case-control data analysis with selection bias. Biometrics 57:1106-12
Paik, M C; Sacco, R; Lin, I F (2000) Bivariate binary data analysis with nonignorably missing outcomes. Biometrics 56:1145-56