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Handling missing data in Stata: Imputation and likelihood ...
IntroductionMultiple ImputationFull information maximum likelihoodConclusionHandling missing data in Stata: Imputation andlikelihood-based approachesRose MedeirosStataCorp LP2016 Swiss Stata Users Group meetingMedeirosHandling missing data in StataIntroductionMultiple ImputationFull information maximum likelihoodConclusionMissing ValuesMissing values are ubiquitous in many disciplinesRespondents fail to fully complete questionnairesFollow-up points are missingEquiptment malfunctionsA number of methods of Handling missing values have beendevelopedMedeirosHandling missing data in StataIntroductionMultiple ImputationFull information maximum likelihoodConclusionTraditional MethodsComplete case analysis analyze only those cases with completedata on some set of variablesPotentially biased unless the complete cases are a random sample ofthe full sampleHot deck picking a fixed value from another observation with thesame covariatesNot necessarily deterministic if there were many observations with thesame covariate patternMean Imputation replacing with a meanRegression
Introduction Multiple Imputation Full information maximum likelihood Conclusion Handling missing data in Stata: Imputation and likelihood-based approaches
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