Showing papers by "Donald B. Rubin published in 1990"
1,428 citations
TL;DR: A brief review of modes of statistical inference for causal effects can be found in this paper for a volume honoring I.J. Good's extensive and creative contributions to statistics, which is a volume dedicated to his life and work.
473 citations
TL;DR: Multiple imputation is applied to a demographic data set with coarse age measurements for Tanzanian children using a simple naive model and a new, relatively complex model that relates true age to the observed values of heaped age, sex, and anthropometric variables.
Abstract: Multiple imputation is applied to a demographic data set with coarse age measurements for Tanzanian children. The heaped ages are multiply imputed with plausible true ages using (a) a simple naive model and (b) a new, relatively complex model that relates true age to the observed values of heaped age, sex, and anthropometric variables. The imputed true ages are used to create valid inferences under the models and compare inferences across models, thereby revealing sensitivity of inferences to prior specifications, from naive to complex. In addition, diagnostic analyses applied to the imputed data are used to suggest which models appear most appropriate. Because it is not clear just what set of heaping intervals should be used, the models are applied under various assumptions about the heaping: rounding (to the nearest year or half year) versus a combination of rounding and truncation as practiced in the United States, and medium versus wide heaping interval sizes. The most striking conclusions ar...
193 citations
Journal Article•
TL;DR: In this article, multiple imputation is applied to a demographic data set with coarse age measurements for Tanzanian children, where the heaped ages are multiply imputed with plausible true ages using a simple naive model and a relatively complex model that relates true age to the observed values of heaped age, sex, and anthropometric variables.
Abstract: Multiple imputation is applied to a demographic data set with coarse age measurements for Tanzanian children. The heaped ages are multiply imputed with plausible true ages using (a) a simple naive model and (b) a new, relatively complex model that relates true age to the observed values of heaped age, sex, and anthropometric variables. The imputed true ages are used to create valid inferences under the models and compare inferences across models, thereby revealing sensitivity of inferences to prior specifications, from naive to complex. In addition, diagnostic analyses applied to the imputed data are used to suggest which models appear most appropriate. Because it is not clear just what set of heaping intervals should be used, the models are applied under various assumptions about the heaping: rounding (to the nearest year or half year) versus a combination of rounding and truncation as practiced in the United States, and medium versus wide heaping interval sizes. The most striking conclusions ar...
2 citations