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A new framework for managing and analyzing multiply imputed data in Stata AgEcon
Carlin, John B.; Galati, John C.; Royston, Patrick.
A new set of tools is described for performing analyses of an ensemble of datasets that includes multiple copies of the original data with imputations of missing values, as required for the method of multiple imputation. The tools replace those originally developed by the authors. They are based on a simple data management paradigm in which the imputed datasets are all stored along with the original data in a single dataset with a vertically stacked format, as proposed by Royston in his ice and micombine commands. Stacking into a single dataset simplifies the management of the imputed datasets compared with storing them individually. Analysis and manipulation of the stacked datasets is performed with a new prefix command, mim, which can accommodate data...
Tipo: Article Palavras-chave: Mim; Mimstack; Ice; Micombine; Miset; Mifit; Multiple imputation; Missing data; Missing at random; Research Methods/ Statistical Methods.
Ano: 2008 URL: http://purl.umn.edu/120928
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Review of An Introduction to Stata for Health Researchers by Juul AgEcon
Carlin, John B..
Tipo: Article Palavras-chave: Learning Stata; Introductory biostatistics; Epidemiological statistics; Health sciences; Research Methods/ Statistical Methods.
Ano: 2006 URL: http://purl.umn.edu/119246
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Standardizing anthropometric measures in children and adolescents with new functions for egen AgEcon
Vidmar, Suzanna; Carlin, John B.; Hesketh, Kylie; Cole, Tim.
A new function for egen has been developed to allow transformation of child anthropometric data to z-scores using the LMS method and the reference data available from the 1990 British Growth Reference and the 2000 US CDC Growth Reference. An additional function allows for children to be categorized according to body mass index (weight/height2) using international cutoff points recommended by the Childhood Obesity Working Group of the International Obesity Taskforce.
Tipo: Journal Article Palavras-chave: Z-scores; LMS; Egen; Research Methods/ Statistical Methods.
Ano: 2004 URL: http://purl.umn.edu/116210
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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
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