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Estimation of bias-corrected intraclass correlation coefficient for unbalance...
Intraclass correlation coefficient for data in a clustered study is traditionally estimated from a one-way random-effects model. This model assumes normality for the random... -
Bias Correction for Replacement Samples in Longitudinal Research
Missing data are commonly encountered problem in longitudinal research. One way researchers handle missing data is through the use of supplemental samples (i.e., the addition of... -
Scalable module detection for attributed networks with applications to breast...
The objective of network module detection is to identify groups of nodes within a network structure that are tightly connected. Nodes in a network often have attributes (aka... -
dedup_wf_001--5616457cd6557bbe26d978211488ac58
The sample selection bias problem occurs when the outcome of interest is only observed according to some selection rule, where there is a dependence structure between the... -
Mini-Batch Metropolis–Hastings With Reversible SGLD Proposal
Traditional Markov chain Monte Carlo (MCMC) algorithms are computationally intensive and do not scale well to large data. In particular, the Metropolis–Hastings (MH) algorithm...
