Journal of Social Service Research · 1985 · 33 citations · 0 references
Public HealthBiostatisticsSocial WorkExperimental DesignOutcomes ResearchStatisticsExperimental EvaluationHypothesis TestingMeasurement ErrorStatistical AnalysisStudy DesignAssumption Of Common ErrorClinical Significance AssessmentClinical Significance CriteriaExperimental Results InterpretationExperimental StudiesExplained VarianceStatistical ErrorWithin-study Variance
This article discusses a common statistical error that frequently appears in efforts to assess the importance of experimental outcomes in the social work practice and research literature, failure to provide proportions of explained variance in a manner which permits judgements as to their substantive importance or clinical significance. It then briefly describes a partial remedy and presents practical statistical formulas which research consumers can use to calculate proportions of explained variance when published reports fail to provide this information.