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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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