High dimensional variable selection with clustered data: an application of random multivariate survival forests for detection of outlier medical device components
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Statistical Computation and Simulation"
DOI: 10.1080/00949655.2019.1584198
Abstract: ABSTRACT In many medical studies patients are nested or clustered within doctor. With many explanatory variables, variable selection with clustered data can be challenging. We propose a method for variable selection based on random forest… read more here.
Keywords: selection clustered; device components; clustered data; variable selection ... See more keywords
Optimal nonparametric estimator of the area under ROC curve based on clustered data
Sign Up to like & getrecommendations! Published in 2019 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2018.1563176
Abstract: Abstract In diagnostic trials, clustered data are obtained when several subunits of the same patient are observed. Intracluster correlations need to be taken into account when analyzing such clustered data. A nonparametric method has been… read more here.
Keywords: estimator; optimal nonparametric; area; clustered data ... See more keywords
Saddlepoint approximation for weighted log-rank tests based on block truncated binomial design
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Biopharmaceutical Statistics"
DOI: 10.1080/10543406.2022.2108825
Abstract: ABSTRACT Clustered data frequently occur in biomedical research fields and clinical trials. The log-rank tests are widely used for two-independent samples of clustered data tests. The randomized block design and truncated binomial design are used… read more here.
Keywords: log rank; approximation; rank tests; truncated binomial ... See more keywords
Marginal structural models for multilevel clustered data.
Sign Up to like & getrecommendations! Published in 2022 at "Biostatistics"
DOI: 10.1093/biostatistics/kxac027
Abstract: Marginal structural models (MSMs), which adopt inverse probability treatment weighting in the estimating equations, are powerful tools to estimate the causal effects of time-varying exposures in the presence of time-dependent confounders. Motivated by the Conservation… read more here.
Keywords: models multilevel; time; clustered data; multilevel clustered ... See more keywords
How to Report Data on Bilateral Procedures and Other Issues with Clustered Data: The CLUDA Reporting Guidelines
Sign Up to like & getrecommendations! Published in 2022 at "Plastic and Reconstructive Surgery"
DOI: 10.1097/prs.0000000000009293
Abstract: Background: Research in plastic surgery often includes bilateral procedures. This gives rise to issues with clustered data. Clustering is when individual data points within a data set are internally related. However, many authors do not… read more here.
Keywords: surgery; bilateral procedures; data cluda; reporting guidelines ... See more keywords
Estimation and Testing of Wilcoxon-Mann-Whitney Effects in Factorial Clustered Data Designs
Sign Up to like & getrecommendations! Published in 2022 at "Symmetry"
DOI: 10.3390/sym14020244
Abstract: Clustered data arise frequently in many practical applications whenever units are repeatedly observed under a certain condition. One typical example for clustered data are animal experiments, where several animals share the same cage and should… read more here.
Keywords: mann whitney; wilcoxon mann; estimation; clustered data ... See more keywords