Generation

generate functionTue, 18 Apr 2023

> indvar_FODs$Condition_FODs<-factor(indvar_FODs$Condition_FODs, levels=c("A", "B", "C", "D"), labels=c("A", "B", "C", "D")) > indvar_FODs$developmentaldisorder_FODs<-factor(indvar_FODs$developmentaldisorder_FODs, levels=c("No", "Yes"), labels=c("No", "Yes")) > indvar_FODs$categorical_FOD_FODs<-factor(indvar_FODs$categorical_FOD_FODs, levels=c("ascending", "identity", "descending"), labels=c("ascending", "identity", "descending")) > model1 <- glmer(categorical_FOD_FODs ~ Condition_FODs + developmentaldisorder_FODs + Condition_FODs:developmentaldisorder_FODs + (1|subject_FODs), + data = indvar_FODs, family = "binomial", control = glmerControl(optimizer = "bobyqa")) boundary (singular) fit: see help('isSingular') what should I do now?

> indvar_FODs$Condition_FODs<-factor(indvar_FODs$Condition_FODs, levels=c("A", "B", "C", "D"), labels=c("A", "B", "C", "D")) > indvar_FODs$developmentaldisorder_FODs<-factor(indvar_FODs$developmentaldisorder_FODs, levels=c("No", "Yes"), labels=c("No", "Yes")) > indvar_FODs$categorical_FOD_FODs<-factor(indvar_FODs$categorical_FOD_FODs, levels=c("ascending", "identity", "descending"), labels=c("ascending", "identity", "descending")) > model1 <- glmer(categorical_FOD_FODs ~ Condition_FODs + developmentaldisorder_FODs + Condition_FODs:developmentaldisorder_FODs + (1|subject_FODs), +

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