Objective Findings from family-based analyses, such as sibling comparisons, are often reported using only odds ratios or hazard ratios. We demonstrate how this can be improved upon by applying the marginalized between-within framework.

Study Design and Setting We provide an overview of sibling comparison methods and the marginalized between-within framework, which enables estimation of absolute risks and clinically relevant metrics while accounting for shared familial confounding. We illustrate the approach using Swedish registry data to examine the association between maternal smoking and infant mortality, estimating absolute risk differences, average treatment effects, attributable fractions, and numbers needed to harm (or treat).

Results The marginalized between-within model decomposes effects into within-and between-family components while applying a global baseline across all families. Although it typically yields similar relative estimates to conditional logistic or stratified Cox regression, the model’s specification of a baseline enables the estimation of absolute measures. In the applied example, absolute measures provided more interpretable and policy-relevant insights than relative estimates alone. Code for implementation in Stata and R is provided.

Conclusion The marginalized between-within framework may strengthen the interpretability of family-based analysis by enabling absolute and policy-relevant estimates for both binary and time-to-event outcomes, moving beyond the limitations of solely relying on relative effect measures.

Key Findings

Findings from sibling analyses are typically presented using only relative measures, such as odds ratios or hazard ratios, limiting interpretability.

This study illustrates how the marginalized between-within framework can be used to derive clinically relevant absolute effect measures while adjusting for shared familial confounding.

What this adds to what was known?

Unlike conventional methods, this approach enables estimation of absolute risks, average treatment effects, attributable fractions, and numbers needed to treat or harm—using standard software—while accounting for unmeasured familial con-founding.

What is the implication and what should change now?

Researchers conducting sibling comparisons should consider adopting the marginalized between-within framework to report both relative and absolute effect measures.

This shift could enhance the clinical and public health relevance of family-based designs by improving interpretability and communication of findings.

The authors have declared no competing interest.

The study was funded by the National Institutes of Health (1R01NS107607-01A1) and the Swedish Society for Medical Research (PG-24-0427). The funders had no role in the design of the study, data management, data analysis, interpretation of findings, and the decision to submit the article for publication.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The applied analysis was approved by the Regional Ethical Review Board in Stockholm (2020-05516).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

The data used for the applied example are publicly unavailable according to regula-tions under Swedish law. Readers interested in obtaining microdata may seek similar ap-provals and inquire through Statistics Sweden.