[PDF] Top 20 Outcome-sensitive multiple imputation: a simulation study
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Outcome-sensitive multiple imputation: a simulation study
... incomplete outcome is prefera- ble to excluding the relevant ...the outcome is imputed, will be assessed as a best practice alternative to C and ...second outcome which is correlated to our ... See full document
13
Variable selection under multiple imputation using the bootstrap in a prognostic study
... Single imputation, such as mean imputation or imputation based on linear regression, leads to incorrect statistical tests because the complete-data analysis does not account for uncertainty created ... See full document
10
Multiple imputation for estimation of an occurrence rate in cohorts with attrition and discrete follow-up time points: a simulation study
... Multiple imputation was evaluated here under the assumption that the probability of drop-out immediately after time point t depended on the observed covariate at time point t ...treatment. Multiple ... See full document
7
Multiple imputation of multiple multi item scales when a full imputation model is infeasible
... applying multiple imputation by chained equa- tions to the individual scale items is computationally ...of multiple imputation by chained equations which imputes the individual scale items but ... See full document
15
Would changing the selection process for GP trainees stem the workforce crisis? A cohort study using multiple imputation and simulation
... Changing the selection process alone would have a rela- tively small, although perhaps useful effect on the num- ber of trainees entering the GP Register. Of the selection processes modelled in this study, using ... See full document
8
Multiple imputation methods for handling missing values in a longitudinal categorical variable with restrictions on transitions over time: a simulation study
... PMM imputation produced the least biased estimates when compared to other MI methods irre- spective of whether restrictions were ...the imputation model when computing the predictive distance. A ... See full document
14
The use of fully conditional specification of multiple imputation and inverse probability weighting to model the pulmonary disease occurrence in survey data with non response
... using multiple imputation (MI) and inverse probability weighting (IPW) ...Generally, multiple imputation has the ability to draw multiple values from plausible predictive distribution ... See full document
8
Dealing with missing data in the Center for Epidemiologic Studies Depression self-report scale: a study based on the French E3N cohort
... present study investigated MVs in the CES-D scale, a validated and easy-to-use tool, commonly used to iden- tify ...qualitative study showed that none of the women contacted declared that they were ... See full document
11
Diagnosing problems with imputation models using the Kolmogorov-Smirnov test: a simulation study
... current study, ...these multiple p-values. In both the LSAC application and the simulation study, we performed 20 imputations and summarized the multiple p-values using medians (using ... See full document
9
Nested multiple imputation in large-scale assessments
... a simulation study to explore the impact of missing values on background variables on proficiency estimates when missing values on back- ground variables were dummy coded, focusing on the estimation of ... See full document
18
A comparison of multiple imputation methods for handling missing values in longitudinal data in the presence of a time-varying covariate with a non-linear association with time: a simulation study
... and multiple imputation (MI) ...replicated multiple times and missing values are replaced by plausible values drawn from a posterior distribution according to a suitable im- putation model based on ... See full document
11
Multiple imputation for handling missing outcome data when estimating the relative risk
... this study was to contrast the per- formance of MVNI and FCS for handling missing out- come data when estimating the relative ...to imputation model misspeci- fication was not evident ... See full document
10
Imputation strategies when a continuous outcome is to be dichotomized for responder analysis: a simulation study
... and multiple imputation ...the imputation model to generate M complete ...The imputation model must be congenial, ...the imputation model can include variables predictive of missingness ... See full document
11
Multiple Imputation of Missing Data: A Simulation Study on a Binary Response
... that multiple imputations generally perform particu- larly well ...While multiple imputations were ori- ginnally developed for larger datasets with small propor- tions of missing data, ...using ... See full document
9
Comparative Analysis Of Different Imputation Techniques For Handling Missing Dataset
... practically Imputation plays a major role in handling missing ...single imputation or multiple ...single imputation methods to handle missing data like Mean, Median, ... See full document
5
Methodological challenges in building composite indexes: Linking theory to practice
... simple imputation, or inverse correlation would have been adopted; China would gain 7 positions in the world rank if I would have simply used a different normalization techniques; Morocco may have been better off ... See full document
11
Principal Longevity, Leadership Behaviors, and Student Academic Achievement
... within imputation vari- ances and between imputation ...the multiple imputation m does not necessarily to be large, we choose m = 10 in our study as suggested by Pan ... See full document
59
Multiple Imputation by Chained Equations for Social Data
... It is assumed that the vector = ( , , … , ) is a k−dimensional random variable, subject to the k−variate distribution ( | ). The matrix = ( , , … , ) with missing data is the independent and identically distributed ... See full document
6
Multiple imputation for completion of a national clinical audit dataset.
... the imputation model to reduce or remove the dupli- cated information in the prediction ...of multiple deprivation (IMD) score as predictors for the same ...the imputation of one ... See full document
20
A Comparative Study between Multiple Imputation Method and Regression Imputation Method of Estimation of Missing Data
... this study revealed that the ...of multiple imputation method was lower than the ...regression imputation method. These results were consistent with MAE of multiple imputation ... See full document
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