  Case-mix heterogeneity across studies complicates meta-analyses. As a result
of this, treatments that are equally effective on patient subgroups may appear
to have different effectiveness on patient populations with different case mix.
It is therefore important that meta-analyses be explicit for what patient
population they describe the treatment effect. To achieve this, we develop a
new approach for meta-analysis of randomized clinical trials, which use
individual patient data (IPD) from all trials to infer the treatment effect for
the patient population in a given trial, based on direct standardization using
either outcome regression (OCR) or inverse probability weighting (IPW).
Accompanying random-effect meta-analysis models are developed. The new approach
enables disentangling heterogeneity due to case mix from that due to beyond
case-mix reasons.

Applications;Methodology