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      Methodological problems in the retrospective computation of responsiveness to change: the lesson of Cronbach.

      Journal of Clinical Epidemiology
      Computer Simulation, Data Interpretation, Statistical, Humans, Reproducibility of Results, Research Design, Retrospective Studies, Treatment Outcome

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          Abstract

          To examine the relation between responsiveness coefficients derived directly from a calculation of average change resulting from a treatment intervention (Responsiveness-Treatment or RT) and those derived from retrospective analysis of changed and unchanged groups (Responsiveness Retrospective or RR) based on a global measure of change. Two approaches were used. First, we used simulation methods to examine the analytical relationship between the RT and RR coefficients. We then located eight studies where it was possible to compute both RT and RR coefficients. As anticipated from theoretical arguments, the RR coefficients were larger than the RT coefficients (1.50 versus 0.41, p < .0001). Within study there was no predictable relationship between the two indices. Across studies, the magnitude of the RR coefficient was strongly related to the correlation with the retrospective global scale, and unrelated to the magnitude of the RT coefficient. The simulated curves fit well with the observed data, and substantiated the observation that the relation between RT and RR coefficients is complex and only weakly related to the size of the treatment effect. Retrospective methods of computing responsiveness yield little information about the ability of an instrument to detect treatment effects, and should not be used as a basis for choice of an instrument for applications to clinical trials.

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          Relation of implicit theories to the construction of personal histories.

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            A methodological framework for assessing health indices

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              Health status measures: strategies and analytic methods for assessing change scores.

              Over the last 15 years, numerous self-report health status measures have appeared in the literature. An important parallel development has been the development of numerous strategies for assessing change in health status over time. The purpose of this article is to summarize and critique the more common design and analytic strategies for assessing the meaningfulness of change over time. Five commonly reported designs are presented, critiqued, and depicted using examples from the literature. Methods for analyzing results are reviewed and illustrated using two data sets. Insights into comparing competing health status measures are provided. In summary, the article suggests that some designs and analytic strategies are more adept than others at assessing change and that these methods should be considered when planning sensitivity-to-change studies.
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                Author and article information

                Journal
                9291871
                10.1016/S0895-4356(97)00097-8

                Chemistry
                Computer Simulation,Data Interpretation, Statistical,Humans,Reproducibility of Results,Research Design,Retrospective Studies,Treatment Outcome

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