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 -- View this message in context: http://r.789695.n4.nabble.com/additive-interaction-for-a-dichotomous-dependent-variable-i-e-risk-difference-tp4635842p4649989.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
