The measurement of change in well-being in a longitudinal study of pre- and post-retirees

Marie P. Beaudet

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Aging and Gerontology Research Psychometric Methodologies and Testing Retirement, Disability, and Employment

Abstract

The primary focus of this dissertation is an empirical investigation of three approaches to the measurement of longitudinal change. For the present study, difference scores, residual change scores, and percentage gain scores are compared to determine if their use results in similar findings when the relationships between three resource areas (health, social, and financial) and subjective well-being are analyzed. The propositions which are tested were derived from current aging theories. Meta-analysis procedures were employed to synthesize past research findings in gerontology. The data which were analyzed are those of the Longitudinal Retirement History Study (LRHS), a research project sponsored by the Social Security Administration. The sample consists of 8922 continuers who participated in the 1969, 1971, and 1973 waves of data collection. Findings from the meta-analysis suggest that the correlation coefficients calculated from the LRHS data on the relationship between subjecive well-being and the areas of health resources and social resources are similar to those of other aging studies. The relationship between measures of financial resources and subjective well-being is stronger for the LRHS respondents than that reported in other aging studies. The results on the analysis of longitudinal change indicate that change in health resources and in financial resources are significant predictors of subjective well-being at a later-point-in-time and of change in subjective well-being. For the present study, change in social resources contributes little to the regression equations. The three selected approaches to the measurement of change rank individuals similarly on the construct of change. However, the use of difference scores, residual change scores, and percentage gain scores does not always result in similar findings when multivariate procedures are used. Residual change scores appear to possess a number of advantages. They tend, however, to be strongly related to the time 2 scores from which they are derived, a phenomenon not emphasized in the measurement of change literature. Improving the reliability of measures, allowing adequate time for change to occur, and using sample sizes which are large are suggested to maximize the possibility of obtaining correlation coeffecients based on change scores which are large and stable.