Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
416783 | Computational Statistics & Data Analysis | 2013 | 15 Pages |
Abstract
The explanation of heterogeneity when combining different studies is an important issue in meta analysis. Besides including a heterogeneity parameter in the analysis, it is also important to understand the possible causes of heterogeneity. A possibility is to incorporate study-specific covariates in the model that account for between-trial variability. This leads to the random effects meta regression model. Commonly used methods for constructing confidence intervals for the regression coefficients are examined and two new methods based on generalised inference principles are proposed. The different methods are compared by an extensive simulation study with respect to coverage probability and average length.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Thomas Friedrich, Guido Knapp,