Subgroup analysis
Subgroup analysis partitions studies by a categorical label, such as dose group, design, region, risk-of-bias stratum, or population category. Coventra's optional extraction module adds subgroup fields so rows can be stratified without overloading the basic extraction sheet.
A subgroup model estimates pooled effects within categories and may compare between-subgroup differences. The comparison is observational at the study level unless subgroup membership was randomized or prespecified in a design that supports causal interpretation.
Meta-regression formula
A simple random-effects meta-regression can be written as y_i = beta_0 + beta_1*x_i + u_i + e_i, where y_i is the study effect, x_i is a study-level covariate, u_i is the between-study random effect, and e_i is within-study sampling error.
Coventra's meta-regression uses a selected study-level covariate and the fitted meta-analysis. When no covariate is provided, the default is study year, but publication workflows should explicitly select a meaningful covariate.
The residual heterogeneity tau^2_residual describes remaining between-study variance after the moderator. It does not prove that the moderator is causal.
Changeable settings
- The optional extraction module can be enabled before extraction or later from the extraction analysis plan.
- The covariate name is user-selectable in the meta-regression request.
- The same effect measure, binary method, tau estimator, HKSJ setting, confidence level, SMD method, and plot options can be carried into moderator analyses.
- Bubble plot rendering uses plot options for colors and display.
Main limitations
- Study-level meta-regression cannot estimate participant-level effect modification.
- Moderator analysis is usually underpowered with few studies.
- Multiple exploratory moderators inflate false-positive risk.
- Covariates extracted inconsistently across studies can create artificial signals.
- A single influential study can drive a moderator coefficient.
Reporting checklist
- State whether each subgroup or moderator was prespecified.
- Report the number of studies per subgroup or across the covariate range.
- Describe how missing moderator values were handled.
- Report the model, covariate scale, coefficient, confidence interval, p-value if used, and residual heterogeneity.
- Label exploratory moderator findings as exploratory.