This paper stresses the links that exist between concepts that are used in the theory of model reduction and concepts that arise in the missing data literature. This connection motivates the extension of the missing at random (MAR) and the missing completely at random (MCAR) concepts from a static setting, as introduced by Rubin (1976), to the case of dynamic panel data models. Using this exten...

OBJECTIVE To describe and illustrate missing data mechanisms (MCAR, MAR, NMAR) and missing data techniques (MDTs) and offer recommended best practices for addressing missingness. METHOD We simulated data sets and employed ad hoc MDTs (deletion techniques, mean substitution) and sophisticated MDTs (full information maximum likelihood, Bayesian estimation, multiple imputation) in linear regress...

Missing data are ubiquitous in clinical epidemiological research. Individuals with missing data may differ from those with no missing data in terms of the outcome of interest and prognosis in general. Missing data are often categorized into the following three types: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). In clinical epidemiological resea...

In this research, the aim was to examine effects of Markov Chain Monte Carlo (MCMC), multiple imputation (MI), and expectation maximization (EM), all methods coping with missing data in mixed type tests including dichotomous polytomous items, on differential item functioning (DIF). The study carried out a complete set consisting scores 1160 students who took booklet number 9 science test Trends...

Traditional classification techniques such as decision trees and RIPPER use heuristic search methods to find a small subset of patterns. In recent years, a promising new approach that mainly uses association rule mining in classification called associative classification has been proposed. Most associative classification algorithms adopt the exhaustive search method presented in the famous Apri...

Test of homogeneity of covariances (or homoscedasticity) among several groups has many applications in statistical analysis. In the context of incomplete data analysis, tests of homoscedasticity among groups of cases with identical missing data patterns have been proposed to test whether data are missing completely at random (MCAR). These tests of MCAR require large sample sizes n and/or large ...

The shutoff mechanisms of the rod visual transduction cascade involve G-protein-coupled receptor (GPCR) kinase 1 (GRK1) phosphorylation of light-activated rhodopsin (R*) followed by rod arrestin binding. Deactivation of the cone phototransduction cascade in the mammalian retina is delineated poorly. In this study we sought to explore the potential mechanisms underlying the quenching of the phot...