Erratum: Robust variance estimation in meta-regression with dependent effect size estimates

Erratum: Robust variance estimation in meta-regression with dependent effect size estimates.

Conventional meta-analytic techniques rely on the assumption that effect size estimates from different studies are independent and have sampling distributions with known conditional variances. The independence assumption is violated when studies produce several estimates based on the same individuals or there are clusters of studies that are not independent (such as those carried out by the sam...

Title: Using Robust Variance Estimation to Combine Multiple Regression Estimates with Meta- Analysis

Title: Using Robust Variance Estimation to Combine Multiple Regression Estimates with Meta- Analysis Authors and Affiliations:

Title Page Not included in page count. Abstract Body Limit 4 pages single-spaced.

Robust Estimation in Linear Regression with Molticollinearity and Sparse Models

‎One of the factors affecting the statistical analysis of the data is the presence of outliers‎. ‎The methods which are not affected by the outliers are called robust methods‎. ‎Robust regression methods are robust estimation methods of regression model parameters in the presence of outliers‎. ‎Besides outliers‎, ‎the linear dependency of regressor variables‎, ‎which is called multicollinearity...

for tests of moderators and model fit in robust variance estimation in meta - regression

Title Page Title: Small-sample adjustments for tests of moderators and model fit in robust variance estimation in meta-regression Abstract Body Background / Context: Randomized experiments are commonly used to evaluate the effectiveness of educational interventions. The main focus in randomized experiments is often on the average treatment effect across all participants in the study, yet when t...