Survival analysis with unreliable endpoints.
There exists a current interest in the application of survival analysis methodology to evaluate differences in latencies of response to psychological or psychopharmacological treatment modalities. However, unreliability in the measurement of treatment responses in such research poses a problem. Two methods of defining the "discrete endpoint" that is required for survival analysis are compared regarding power of tests of significance for differences in survival curves. Discrete endpoints defined by regression equations fitted to all available data for each subject provided greater power when entered into survival analysis than did endpoints dependent only on individual measurements. While this may not surprise statisticians, no examples of the use of regression estimates for survival analysis endpoints have been identified in reports of previous clinical trials nor in discussions concerning potential applications of survival analysis methodology in psychiatric research.
Overall
J E
JE
Department of Psychiatry and Behavioral Sciences, University of Texas Medical School at Houston 77030, USA.
Atlas
R S
RS
D000704:Analysis of Variance; D006801:Humans; D001523:Mental Disorders / Q000188:drug therapy*; D015233:Models, Statistical; D009010:Monte Carlo Method; D011581:Psychological Tests / Q000706:statistics & numerical data; D011619:Psychotropic Drugs / Q000627:therapeutic use*; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D012044:Regression Analysis; D015203:Reproducibility of Results; D016019:Survival Analysis; D016896:Treatment Outcome
D011619:Psychotropic Drugs