60 citations · 68 across the 15 of their papers we have counts for
15 papers
Point and interval estimators of a changepoint in stochastical dominance between two distributions
Elena Kulinskaya, David C. Hoaglin
For differences between means of continuous data from independent groups, the customary scale-free measure of effect is the standardized mean difference (SMD). To justify use of SM…
Simulations for estimation of random effects and overall effect in three-level meta-analysis of standardized mean differences using constant and inverse-variance weights
Elena Kulinskaya, David C. Hoaglin
We consider a three-level meta-analysis of standardized mean differences. The standard method of estimation uses inverse-variance weights and REML/PL estimation of variance compone…
Simulations for Meta-analysis of Magnitude Measures
Elena Kulinskaya, David C. Hoaglin
Meta-analysis aims to combine effect measures from several studies. For continuous outcomes, the most popular effect measures use simple or standardized differences in sample means…
Simulations for estimation of heterogeneity variance and overall effect with constant and inverse-variance weights in meta-analysis of difference in standardized means (DSM)
Elena Kulinskaya, David C. Hoaglin
When the individual studies assembled for a meta-analysis report means (, ) for their treatment (T) and control (C) arms, but those data are on different scales or come f…
Associations Between Natural Language Processing (NLP) Enriched Social Determinants of Health and Suicide Death among US Veterans
Avijit Mitra, Richeek Pradhan, Rachel D Melamed +8
Importance: Social determinants of health (SDOH) are known to be associated with increased risk of suicidal behaviors, but few studies utilized SDOH from unstructured electronic he…
Simulations for estimation of heterogeneity variance in constant and inverse variance weights meta-analysis of log-odds-ratios
Elena Kulinskaya, David C. Hoaglin
A number of popular estimators of the between-study variance, , are based on the Cochran's statistic for testing heterogeneity in meta analysis. We introduce new point and…
Simulations for the Q statistic with constant and inverse variance weights for binary effect measures
Elena Kulinskaya, David C. Hoaglin
Cochran's statistic is routinely used for testing heterogeneity in meta-analysis. Its expected value (under an incorrect null distribution) is part of several popular estimator…
Simulation study of Q statistic with constant weights for testing and estimation of heterogeneity of standardized mean differences in meta-analysis
Ilyas Bakbergenuly, David C. Hoaglin, Elena Kulinskaya
Cochran's statistic is routinely used for testing heterogeneity in meta-analysis. Its expected value is also used for estimation of between-study variance . Cochran's ,…
Simulations for a Q statistic with constant weights to assess heterogeneity in meta-analysis of mean difference
Elena Kulinskaya, David C. Hoaglin, Joseph Newman +1
A variety of problems in random-effects meta-analysis arise from the conventional statistic, which uses estimated inverse-variance (IV) weights. In previous work on standardize…
Exploring Consequences of Simulation Design for Apparent Performance of Statistical Methods. 2: Results from simulations with normally and uniformly distributed sample sizes
Elena Kulinskaya, David C. Hoaglin, Ilyas Bakbergenuly
This report continues our investigation of effects a simulation design may have on the conclusions on performance of statistical methods. In the context of meta-analysis of log-odd…
Exploring Consequences of Simulation Design for Apparent Performance of Statistical Methods. 1: Results from simulations with constant sample sizes
Elena Kulinskaya, David C. Hoaglin, Ilyas Bakbergenuly
Contemporary statistical publications rely on simulation to evaluate performance of new methods and compare them with established methods. In the context of meta-analysis of log-od…
Simulation study of estimating between-study variance and overall effect in meta-analyses of log-response-ratio for lognormal data
Ilyas Bakbergenuly, David C. Hoaglin, Elena Kulinskaya
Methods for random-effects meta-analysis require an estimate of the between-study variance, . The performance of estimators of (measured by bias and coverage) affects th…
Simulation study of estimating between-study variance and overall effect in meta-analyses of mean difference
Ilyas Bakbergenuly, David C. Hoaglin, Elena Kulinskaya
Methods for random-effects meta-analysis require an estimate of the between-study variance, . The performance of estimators of (measured by bias and coverage) affects th…
Simulation study of estimating between-study variance and overall effect in meta-analysis of standardized mean difference
Ilyas Bakbergenuly, David C. Hoaglin, Elena Kulinskaya
Methods for random-effects meta-analysis require an estimate of the between-study variance, . The performance of estimators of (measured by bias and coverage) affects th…
Simulation study of estimating between-study variance and overall effect in meta-analysis of odds-ratios
Ilyas Bakbergenuly, David C. Hoaglin, Elena Kulinskaya
Random-effects meta-analysis requires an estimate of the between-study variance, . We study methods of estimation of and its confidence interval in meta-analysis of odds…