> library(multcomp) > > logit<-glm(categorical_FOD_FODs ~ Condition_FODs + Language_used_FODs, + data = indvar_FODs, + family = binomial(link = "logit")) > summary(logit) Call: glm(formula = categorical_FOD_FODs ~ Condition_FODs + Language_used_FODs, family = binomial(link = "logit"), data = indvar_FODs) Deviance Residuals: Min 1Q Median 3Q Max -1.258 -1.157 -1.117 1.198 1.239 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 0.02715 0.09178 0.296 0.7674 Condition_FODsB -0.17148 0.09832 -1.744 0.0811 . Condition_FODsC -0.14466 0.09814 -1.474 0.1405 Condition_FODsD -0.12076 0.09831 -1.228 0.2193 Language_used_FODsGerman 0.02854 0.17759 0.161 0.8723 Language_used_FODsHungarian 0.16117 0.17665 0.912 0.3616 Language_used_FODsItalian 0.08189 0.17958 0.456 0.6484 Language_used_FODsTurkish 0.06950 0.08236 0.844 0.3988 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 4603.3 on 3320 degrees of freedom Residual deviance: 4598.5 on 3313 degrees of freedom (199 observations deleted due to missingness) AIC: 4614.5 Number of Fisher Scoring iterations: 3 please report these results in APA style