In this paper, we propose a multiple imputation method for the semiparametric accelerated failure time mixture cure model based on the rank estimation method and the profile likelihood method. Both approaches can be easily implemented in R environment. However, the computation time for the rank ...
Handling missing data in an FFQ: multiple imputation and nutrient intake estimates. Public Health Nutr. 2019;22:1351–60. Article PubMed Google Scholar Kupek E, de Assis MA. The use of multiple imputation method for the validation of 24-h food recalls by part-time observation of dietary ...
In the case of comparing multiple imputation methods, it can be argued when one imputation method leads to substantial bias and hence incorrect inference in subsequent Scientific Reports | 6:21689 | DOI: 10.1038/srep21689 8 www.nature.com/scientificreports/ Biomarkers FAM178A IMAGE:813259 UGP2 ...
2. A multiple-phenotype imputation method for genetic studies[J]. Nature genetics, 2016, 48(4): 466-472. Traits were mean and variance standardized and quantile normalized before analysis. nature.com/articles/ng. 3. Components of genetic associations across 2,138 phenotypes in the UK Biobank ...
Using each method, we generated 20 imputations for the missing values. Finally, we used the R packages lme4 (Bates et al., 2019) and mitml (Grund et al., 2019) to analyze the imputed data sets and pool the results. For comparison, we also included LD. The results are summarized in...
MAGIC: a diffusion-based imputation method reveals gene-gene interactions in single-cell RNA-sequencing data bioRxiv (2017), 10.1101/111591 Published online February 25, 2017 Google Scholar 88 D. Risso, et al. ZINB-WaVE: a general and flexible method for signal extraction from single-cell RNA...
Multiple imputation (MI) accounts for imputation uncertainty that allows for adequate statistical testing. We developed and tested a methodology combining MI with bootstrapping techniques for studying prognostic variable selection. Method In our prospective cohort study we merged data from three different ...
For more information about the method, see: Nassiri, V., Lovik, A., Molenberghs, G., Verbeke, G. (2018). On using multiple imputation for exploratory factor analysis of incomplete data.Behavior Research Methods50, 501–517. doi:10.3758/s13428-017-1013-4 ...
The SPARS method is described in detail in the first article of this theme issue [2]. To assess the longitudinal impact of the SPARS program, which was rolled out nationally in 2012, we assessed per- formance results during the first year of supervision in gov- ernment and private not-...
4 Multiple imputation (MICE): MICE is a statistical method for estimating missing data. First, MICE gen- erates several different complete datasets by simulat- ing each missing value multiple times to reflect the uncertainty in the missing values. Then each com- plete dataset is analysed using ...