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# Indirect Relative Risk Adjustment (IRRAD)

### Description

IRRAD is an Excel spreadsheet that extends the “Axelson adjustment” for binary variables to adjust observed RRs for a (measured or unmeasured) confounding variable when exposure and confounder have multiple categories.  IRRAD allows the User to designate a multiplicative or an additive relative risk (RR) model for the joint association of exposure (X) and confounder (C).  Additionally, the spreadsheet solves linear equations to define those characteristics that a confounder must have to explain fully or partially an observed association.

### Details

The spreadsheet incorporates four approaches to assess confounder effects under either a multiplicative or additive model. These include:

• Binary exposure and binary confounder: a) find the adjusted RR given the observed RR, P(C=1|X=1) and P(C=1|X=0) [or equivalently the observed RR, P(C=1|X=0) and the odds ratio OR(X,C)]; and b) solve for the necessary OR(X,C) given the observed, adjusted and confounder RRs and P(C=1|X=0);
• Categorical exposure and categorical confounder: find the adjusted RRs for each level of exposure given the observed RRs, the confounder distribution at each level of exposure P(C|X) and confounder RRs at the reference level of exposure;
• Categorical exposure and binary confounder: solve for the conditional distribution of the confounder at each level of X, P(C=1|X), given the observed, adjusted and confounder RRs and P(C=1|X=0);
• Categorical exposure and catgorical confounder: solve for the confounder RRs given the observed RRs, the adjusted RRs and P(C|X).

IRRAD includes the data used for the examples in Lubin et al.

### Support

Email: Contact DCEG

### Reference

• Lubin JH, Hauptmann M, Blair A. Indirect adjustment of relative risks of an exposure with multiple categories for an unmeasured confounder. Ann Epidemiol 2018 In Press

Note: IRRAD is currently under review and development for 508-compliance.

• Updated: