Applying permutation tests with adjustment for covariates and attrition weights to randomized trials of health-services interventions.
|Title||Applying permutation tests with adjustment for covariates and attrition weights to randomized trials of health-services interventions.|
|Publication Type||Journal Article|
|Year of Publication||2009|
|Authors||Tang, L, Duan N, Klap R, Asarnow JR, Belin TR|
|Journal||Statistics in medicine|
|Date Published||2009 Jan 15|
|Keywords||Adolescent, Analysis of Variance, Depression, Humans, Intervention Studies, Patient Dropouts, Primary Health Care, Randomized Controlled Trials as Topic, Regression Analysis, Treatment Outcome|
Using a health-services study as an illustrative example of longitudinal randomized field research with the potential for participants to be lost to follow-up, we apply a permutation test where the treatment indicator variable is randomly permuted in the context of regression models with covariates and attrition weighting. The test is applied to a multi-site randomized intervention trial of a quality-improvement program for adolescent depression treatment in primary-care settings, in which regression models were used to assess intervention effects with weights used to adjust for attrition bias. The foundation and motivation for this approach to the analysis are considered with attention to the demands associated with implementing such a strategy. The results from the permutation tests were qualitatively similar to the results obtained from conventional parametric models, and in fact suggested that the significance level from the conventional t-test was understated in this application.
|Alternate Journal||Stat Med|