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	Provedor de dados AgEcon (1) Autor Carlin, John B. (1) Coffey, Carolyn (1) Greenwood, Philip (1) Li, Ning (1) Palavra-chave Missing data (1) Multiple imputation (1) Overall estimates (1) Research Methods/ Statistical Methods (1) Rubin's rule of combination (1) Tipo do documento Journal Article (1) Ano 2003 (1) País United States (1) Idioma Inglês (1)		Ordenar por:  Relevância Autor Título Ano Registros recuperados: 1 Primeira ... 1 ... Última Tools for analyzing multiple imputed datasets AgEcon Carlin, John B.; Li, Ning; Greenwood, Philip; Coffey, Carolyn. The method of multiple imputation (MI) is used increasingly for analyzing datasets with missing observations. Two sets of tasks are required in order to implement the method: (a) generating multiple complete datasets in which missing values have been imputed by simulating from an appropriate probability distribution and (b) analyzing the multiple imputed datasets and combining complete data inferences from them to form an overall inference for parameters of interest. An increasing number of software tools are available for task (a), although this is difficult to automate, because the method of imputation should depend on the context and available covariate data. When the quantity of missing data is not great, the sensitivity of results to the imputation... Tipo: Journal Article Palavras-chave: Missing data; Multiple imputation; Rubin's rule of combination; Overall estimates; Research Methods/ Statistical Methods. Ano: 2003 URL: http://purl.umn.edu/116087 Registros recuperados: 1 Primeira ... 1 ... Última

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