Evaluation of the results of a randomized controlled trial : how to define changes between baseline and follow-up
article
The most common way to evaluate the effect of an intervention is to compare the intervention and non-intervention groups regarding the change in the outcome variable between baseline and follow-up; however, there are many different ways to define "changes". The purpose of this article is to demonstrate how different definitions of "change" used in the analysis can influence the results of a study. Two different randomised controlled trials were used as examples. The results of the analysis showed that for continuous outcome variables, analysis of covariance seems to be the most appropriate because it corrects for the phenomenon of regression to the mean. For dichotomous outcome variables, multinomial logistic regression analysis with all possible changes over time as outcome seems to be the most appropriate, especially because of its straightforward interpretation. A different definition of "change" can lead to different results in the evaluation of the effect of an intervention.
Topics
ChangesContinuous outcome variablesDichotomous outcome variablesMultinomial logistic regressionRegression to the meanCovarianceData analysisDietary intakeFollow upIntermethod comparisonMultivariate logistic regression analysisOutcomes researchPhysical activityStatistical analysisAnalysis of VarianceCounselingDietExerciseHumansOccupational HealthRandomized Controlled TrialsResearch DesignTreatment Outcome
TNO Identifier
150873
Source
Journal of Clinical Epidemiology, 57(3), pp. 223-228.
Pages
223-228
Files
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