2014
DOI: 10.1016/j.jclinepi.2013.09.009
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Missing data in a multi-item instrument were best handled by multiple imputation at the item score level

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Cited by 227 publications
(194 citation statements)
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“…Missing data were handled through multiple imputation in the Statistical Package for the Social Sciences (SPSS) 21.0 for participants who completed at least 80% of each measure (Eekhout et al, 2014). Missing data analyses in SPSS 21.0 indicated that 0.61% of data were missing at Week 1 and 0.33% of data were missing at Week 8 for a combined 0.56% of missingness across weeks.…”
Section: Resultsmentioning
confidence: 99%
“…Missing data were handled through multiple imputation in the Statistical Package for the Social Sciences (SPSS) 21.0 for participants who completed at least 80% of each measure (Eekhout et al, 2014). Missing data analyses in SPSS 21.0 indicated that 0.61% of data were missing at Week 1 and 0.33% of data were missing at Week 8 for a combined 0.56% of missingness across weeks.…”
Section: Resultsmentioning
confidence: 99%
“…Multiple imputation (10 imputations) was performed on item level for missing culture items. 28 The imputation model included culture items, sex, discipline and age as predictors. As formal management items could not be answered by everyone, these were not imputed.…”
Section: Discussionmentioning
confidence: 99%
“…The median number of missing tests missing was 3 (IQR 1–8). We dealt with missing neuropsychological test data using multiple imputation of individual test scores with predictive mean matching due to non-normal distributions 20 21. We imputed data of 104 patients with age, sex, MMSE and all available neuropsychological test results as predictors for the multiple imputation.…”
Section: Methodsmentioning
confidence: 99%