The aims of the Clinical Psychopharmacology Computer Laboratory are to provide quantitative and computer support for clinical psychopharmacology research through collaborative participation in projects conducted by investigators in our institutional setting and in other institutions as well. Different levels of involvement in different projects will extend from participation in actual data collection to the providing of specific specialized services such as computer classification of symptom profiles of patients who are research subjects. In addition to collaborative research support functions, activities supported by the grant will include (a) development and/or evaluation of measuring instruments and assessment devices having potential applications in clincal psychopharmacology research, (b) development and/or evaluation of diagnostic criteria and classification procedure for defining research populations, (c) development and/or evaluation of new statistical methods having potential applications in clinical psychopharmacology research. The methodology employed in pursuit of these aims will be statistical or psychometric. Standard statistical methods such as general linear model analysis of variance or covariance, as well as powerful quantitative models for ellucidation of multivariate relationships, are available for use in analysis of clinical data. Monte carlo methods will be relied on heavily in evaluating the performance of statistical tests under conditions simulating those encountered in clinical research, and exact methods will be used to calculate probabilities of Type I an Type II errors in other cases.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH032457-08
Application #
3375336
Study Section
(PCBB)
Project Start
1978-09-01
Project End
1986-08-31
Budget Start
1985-09-01
Budget End
1986-08-31
Support Year
8
Fiscal Year
1985
Total Cost
Indirect Cost
Name
University of Texas Health Science Center Houston
Department
Type
Schools of Medicine
DUNS #
City
Houston
State
TX
Country
United States
Zip Code
77225
Tonidandel, Scott; Overall, John E; Smith, Fraser (2004) Use of resampling to select among alternative error structure specifications for GLMM analyses of repeated measurements. Int J Methods Psychiatr Res 13:24-33
Overall, John E; Tonidandel, Scott (2002) Measuring change in controlled longitudinal studies. Br J Math Stat Psychol 55:109-24
Ahn, C; Overall, J E; Tonidandel, S (2001) Sample size and power calculations in repeated measurement analysis. Comput Methods Programs Biomed 64:121-124
Ahn, C; Tonidandel, S; Overall, J E (2000) Issues in use of SAS PROC.MIXED to test the significance of treatment effects in controlled clinical trials. J Biopharm Stat 10:265-86
Overall, J E; Ahn, C; Shivakumar, C et al. (1999) Problematic formulations of SAS PROC.MIXED models for repeated measurements. J Biopharm Stat 9:189-216
Overall, J E; Atlas, R S (1999) Power of univariate and multivariate analyses of repeated measurements in controlled clinical trials. J Clin Psychol 55:465-85
Overall, J E; Shivakumar, C (1999) Testing differences in response trends across a normalized time domain. J Clin Psychol 55:857-67
Overall, J E; Shobaki, G; Shivakumar, C et al. (1998) Adjusting sample size for anticipated dropouts in clinical trials. Psychopharmacol Bull 34:25-33
Overall, J E; Shobaki, G; Anderson, C B (1998) Comparative evaluation of two models for estimating sample sizes for tests on trends across repeated measurements. Control Clin Trials 19:188-97
Overall, J E (1997) Drop-outs and a random regression model. J Biopharm Stat 7:383-402

Showing the most recent 10 out of 40 publications