Multiple imputation was designed to handle the problem of missing data in public-use data bases where the data-base constructor and the ultimate user are distinct entities. The objective is valid frequency inference for ultimate users who in general have access only to complete-data software and ...
Multiple Imputation •Originated by Donald Rubin (Multiple imputation for nonresponse in surveys, Wiley, 1987; Multiple imputation after 18+ years, Journal of the American Statistical Association,1996, 473-489)•MI is a simulation-based procedure. Its purpose is not to re-create the individual ...
MultipleImputation 系统标签: imputationmultipleedrecdatasetimputeddatasets 1MultipleImputationinSPSSMultipleImputation•OriginatedbyDonaldRubin(Multipleimputationfornonresponseinsurveys,Wiley,1987;Multipleimputationafter18+years,JournaloftheAmericanStatisticalAssociation,1996,473-489)•MIisasimulation-basedprocedure.Itspur...
(StataCorp) September 16, 2011 2 / 45 Chained equations and more in multiple imputation in Stata 12 Brief overview of MI Multiple imputation (MI) is a principled, simulation-based approach for analyzing incomplete data MI procedure 1) replaces missing values with multiple sets of simulated ...
Rubin DB: Multiple imputation after 18+ years. Journal of the American Statistical Association. 1996, 91: 473-489. 10.2307/2291635. Article Google Scholar Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR: A simulation study of the number of events per variable in logistic regression...
(name=app4, setup=new, dir=. ); datain app4; dataout app4_imp; default continuous; categorical sex region racecat_ educat mde_r str_secu; transfer sampleid mde_imp educat_imp str secu mde; multiples 5; seed 876; run; After imputation, the %PUTDATA macro outputs five temporary SAS...
Multiple imputation of missing data values showed no evidence of bias in the comparison of treatments. However, the HRQoL data were substantially weakened in this double-blind trial by poor compliance in questionnaire completion as the study progressed. HRQoL data from the NMSG (Hjorth et al.). ...
For continuous end points, data were treated as missing after rescue medication use or early discontinuation; missing data were imputed using multiple imputation with analysis of covariance, with treatment group, SOLO treatment regimen, randomization strata (disease severity), and SOLO-CONTINUE baseline ...
After slaughter, dissections were performed to measure dressed weight (DW), Abdominal fat weight (AFW), eviscerated weight (EW), the combined weight of the ventriculus and the proventriculus (SW, F2 only)18, all in grams, and intestine length (IL, F9 only) in centimeters. In the F9 ...
In the robustness analysis, with worst-case imputation of missing data points, the difference between the treatment groups was still not significant (HL = 1; 95% CI, −1 to 2; P = .39). Adjusting for the baseline ω-3:ω-6 fatty acid ratio did not yield significant treatment effects...