[R] additive interaction for a dichotomous dependent variable (i.e. risk difference)

Frank Harrell f.harrell at vanderbilt.edu
Sun Nov 18 23:52:08 CET 2012


In many situations the interactions indicated by additive risk models are
false in the sense that they merely reflect restrictions so that risk are in
[0,1].  I tend to prefer models that have no restrictions on the parameters. 
In fact, I think that a test of goodness of fit of a model can be made on
the basis of comparing with another model and seeing which of the two have
the smallest explained variation by interaction terms.
Frank

wouterjohannes wrote
> Dear all,
> 
> For my research I want to test additive interaction for a dichotomous
> dependent variable. Can anyone help me to estimate this in R? 
> 
> Wacholder describes this procedure in the American Journal of Epidemiology
> in 1986 (Binomial regression in GLIM: estimating risk ratios and risk
> differences). He, however, describes macros for GLIM and not for R. Others
> (Uher et al. Journal of Affective disorders. 2011) also use his method and
> describe it as follows: 
> 
> It has been proposed that gene–environment interactions (G×E) should be
> conceptualized as departures from additivity of risks between genetic and
> environmental factors, as such departures most likely correspond to
> biological causal mechanisms involving both genetic and environmental
> factors (Rothman et al., 2008; Schwartz, 2006). To follow this
> recommendation, we tested G×E in a generalized linear model from the
> binomial family with identity link estimating risk differences for binary
> outcomes (Wacholder, 1986).
> 
> My question is: how can I test for additive interaction in R? In the glm
> package the binomial family and identity link do not seem to go together.
> 
> Thanks in advance.
> 
> Best regards,
> 
> Wouter Johannes





-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
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