… , including a multi-parameter approach to detect one or more … The sliding window is used
to evaluate each data point … four distinct datasets using various imputation techniques and the …

… variables and imputed missing values using multiple imputation. … As the purpose of this
study was to evaluate the potential … multi-parameter pooled Wald-test, which is compatible with …

… -transformed for statistical analyses. Missing data were handled with multiple imputation using
… papers recommend a multi-parameter-based approach to evaluate decongestion and to …

… Moreover, the package also offers a function for multiple imputations for missing data, a
compact computer program that is extensible for different estimation methods of users' choice. …

… to impute binary variables and predictive mean matching to impute numeric features. …
SAPS 3—From evaluation of the patient to evaluation of the intensive care unit. Part 2: …

… to create missing not at random imputed values. In the fourth … In a range of simulation
scenarios, multiple imputation of … a brief review of common approaches of handling multiple …

… multi-parameter nonlinear model. Once \(f(\cdot )\) is determined, we can use it to impute in
missing compound property assay data. … The evaluation metric used in this work is the Mean …

… subtyping with multi-parameter flow cytometry (MFC) data. So far… Evaluation of knowledge
transfer To evaluate knowledge … original data, and the quality of the merged data with imputed …

… This novel approach to multi-parameter synthesis provides a … Eleven of the 13 studies had
an assessment-only control … that accurate imputations of study-level missing data across 19 …

… , because it does not respect that test statistics are approximately Gamma distributed. Note
that … -parameter heritability model, but one-step when provided with a multi-parameter model. …