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Distinguishing Changes in Underlying Status from Changes in Measured Status

Karen Bandeen-Roche, Department of Biostatistics, Johns Hopkins University

When longitudinal measurements imperfectly represent intended outcomes, observed changes may result from shifts in the distributions of intended outcomes, or from shifts in the distributions of measurements conditional on intended outcomes. To exemplify the latter phenomenon: persons reporting their health status may increasingly trust an interviewer as acquaintance grows over the course of a study, hence be increasingly willing to report poor health regardless of any underlying decline. This paper proposes a latent variable framework and methodology for assessing changes in underlying status versus changes in the measurement of status. The framework applies to designs that collect multiple measures of an intended outcome concurrently and track all the measures longitudinally.  Identification issues are considered. Results validating the methodology are reported. Methods are exemplified using a battery of self-reported health items collected in a 7-round investigation of disability in older women. The paper's framework recognizes that underlying and measured change cannot be distinguished without strong modeling assumptions; treating such assumptions as quantities to be varied in sensitivity analyses, it is hoped that the proposed methods will inform the degree to which underlying change can be inferred from changes in surrogates of intended outcomes.