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| Registros recuperados: 11 | |
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| 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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| Royston, Patrick. |
| Royston (2004) introduced mvis, an implementation for Stata of MICE, a method of multiple multivariate imputation of missing values under missing-at-random (MAR) assumptions. In a second article, Royston (2005) described ice, an upgrade incorporating various improvements and changes to the software based on personal experience, discussion with colleagues, and user requests. This article describes an update to ice. The changes are less substantial but nevertheless important enough to warrant a brief explanation. The major modification is that the default method of imputing missing values in ice is now by sampling from the posterior predictive distribution rather than by predicted mean matching. The ice system comprises five ado-files: ice, micombine,... |
| Tipo: Journal Article |
Palavras-chave: Ice; Uvis; Multiple imputation; Missing values; Update; Research Methods/ Statistical Methods. |
| Ano: 2005 |
URL: http://purl.umn.edu/117543 |
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| SCHIATTINO,IRENE; VILLEGAS,RODRIGO; CRUZAT,ANDREA; CUENCA,JIMENA; SALAZAR,LORENA; ARAVENA,OCTAVIO; PESCE,BÁRBARA; CATALÁN,DIEGO; LLANOS,CAROLINA; CUCHACOVICH,MIGUEL; AGUILLÓN,JUAN C. |
| Longitudinal studies aimed at evaluating patients clinical response to specific therapeutic treatments are frequently summarized in incomplete datasets due to missing data. Multivariate statistical procedures use only complete cases, deleting any case with missing data. MI and MIANALYZE procedures of the SAS software perform multiple imputations based on the Markov Chain Monte Carlo method to replace each missing value with a plausible value and to evaluate the efficiency of such missing data treatment. The objective of this work was to compare the evaluation of differences in the increase of serum TNF concentrations depending on the 308 TNF promoter genotype of rheumatoid arthritis (RA) patients receiving anti-TNF therapy with and without multiple... |
| Tipo: Journal article |
Palavras-chave: Multiple imputation; Mixed model; TNF polymorphism. |
| Ano: 2005 |
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602005000100002 |
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| Castro Montoya, René. |
| Debido a factores externos a las variables de inter´es, una serie de tiempo puede presentar cambios en la estructura del modelo o en algunos par´ametros, y debido a l´ımitaciones en los instrumentos de medici´on puede presentar tambi´en censura en las observaciones. Por ejem- plo, cuando se monitorean contaminantes del aire, como pueden ser hidrocarburos arom´aticos (PAHs), mon´oxido de carbono (CO), di´oxido de sulfuro (S O2 ), etc., las series de tiempo ob- servadas pueden tener mediciones censuradas y cambios en la estructura del modelo. En esta tesis se propone un modelo bayesiano para series de tiempo con un n´ umero desconocido de puntos de cambio y con algunas observaciones censuradas, donde cada segmento es un proceso autoregresivo de... |
| Tipo: Tesis |
Palavras-chave: Imputación múltiple; Inferencia bayesiana; Algoritmo de Metrópolis; Algoritmo de cadenas de Markov Monte Carlo con saltos reversibles; Doctorado; Estadística; Multiple imputation; Bayesian inference; Metropolis algorithm; Reversible jump Markov chain Monte Carlo algorithm. |
| Ano: 2009 |
URL: http://hdl.handle.net/10521/1396 |
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| Registros recuperados: 11 | |
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