The authors consider copula models for vectors of binary response variables having marginal distributions that depend on covariates through logistic regressions. They show how to test for residual pairwise dependence between responses, given the explanatory variables. The procedure they propose is based on the score statistic derived from the assumed copula structure under the alternative. The authors further argue that conditional dependence can be conveniently modelled with meta-elliptical copulas, which offer a wide range of positive and negative degrees of association. They call on a composite likelihood to estimate the copula parameters and they provide standard error estimates of the same via linearization. They illustrate their results with Canadian data on the presence or absence of various log grades in trees.