'4 Widowed', '5 Divorced', '6 Separated', '7 Never married', '8 Living with partner', '2 Married - spouse not in household', '3 Married - spouse in household unknown', You can solve this problem by using levels(droplevels(NH11$r_maritl)) in constructing your prediction frame, or equivalently EW$xlevels$r_maritl.Р вЂќР вЂћ reproducible example: maritl_levels <- c( '0 Under 14 years', '1 Married - spouse in household', That said, it's mildly surprising that R doesn't do something nice for you like generate NA values automatically. In hindsight this isn't terribly surprising, since you won't be able to predict responses for these levels. Tl dr it looks like you have some levels in your factor that are not represented in your data, that get dropped from the factors used in the model. Р вЂќР вЂЎactor w/ 2 levels '2 No','1 Yes': NA NA 2 NA NA NA NA NA 2 2. Object$xlevels) : factor r_maritl has new levels 0 Under 14 years, Married The Problem is I get the following response:Р вЂќР’В®rror in (Terms, newdata, na.action = na.action, xlev = Never married', '8 Living with partner', '9 Unknown marital status'),Р вЂќР’В¬bind(predEW, predict(EW, type = 'response', Spouse in household unknown', '4 Widowed', '5 Divorced', '6 Separated', '7

Spouse in household', '2 Married - spouse not in household', '3 Married. '3 Married - spouse in household unknown'Р вЂќР’В®id(r_maritl = c( '0 Under 14 years', '1 Married.

R_maritl has the following levels: levels(NH11$r_maritl) Moreover, I want to predict everwrk for each level of r_maritl. I did a logistic regression: EW <- glm(everwrk~age_p + r_maritl, data = NH11, family = 'binomial')

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