BASELINE ADJUSTMENT FOR STATISTICAL EFFICIENCY ON CLINICAL CONTROLLED TRIA

Abstract

In a clinical controlled trial involving repeated measures of continuous outcomes such as quality of life, distress, pain, activity level at baseline and after treatment, the possibilities of analyzing these outcomes can be numerous with quite varied findings. This paper examined four methods of statistical analysis using data from an outcome study of a clinical controlled trial to contrast the statistical power on those with baseline adjustment. In this study, data from a CCT with women with breast cancer were utilized. The experiment (n=67) and control (n=74) were about equal ratio. Four method of analysis were utilized, two using ANOVA for repeated measures and two using ANCOVA. The multivariate between subjects of the combined dependents variables and the univariate between subjects test were examined to make a judgement of the statistical power of each method. The results showed that ANCOVA has the highest statistical power. ANOVA using raw data is the least power and is the worst method with no evidence of an intervention effect even when the treatment by time interaction is statistically significant. In conclusion, ANOVA using raw data is the worst method with the least power whilst ANCOVA using baseline as covariate has the highest statistical power to detect a treatment effect other than method. The second best method as shown in this study was in using change scores of the repeated measures.