logistic regression backwards selection I am somewhat new to R and trying to polish my logistic regression. I am testing if my risk factors(cruise, age, sex, and year) have a significant effect on my dependent variable, MPS infection (named MPS_BINARY). I have a total of four cruises (5, 7, 9, 11), three years, thirteen ages, and two sexes (1 or 0). 
I am able to run the full model with the following command:    
>mylogit<-glm(MPS_BINARY~ AGE * SEX * CRUISE * YEAR, data=mps,family="binomial")

From this I have my p-values, I can now identify significant risk factors and interactions. My data shows a significant p-value for the interaction between cruise 7 and year. Following backwards selection, I now need to run the model again with my original risk factors and significant terms. I am having increasing difficulty isolating cruise 7 from my cruise data to run as an interaction with year. I have tried using the command:
>mylogit<-glm(MPS_BINARY~AGE+SEX+YEAR+CRUISE+mps$CRUISE7*YEAR,data=mps,family="binomial")

But this, of course, does not recognize cruise 7 and I receive the error message: Error in model.frame.default(formula = MPS_BINARY ~ AGE + SEX + CRUISE +  : 
  invalid type (NULL) for variable 'mps$CRUISE7'.
My question is how can I run my logistic regression with all of my risk factors, and the significant interaction between year and cruise 7? I cannot figure out how to isolate only cruise 7 for the interaction with year. Please let me know if you need more information, thank you! 
 A: You probably shouldn't do this. A general rule of thumb advises against thinking of categorical variables as their individual levels during model selection.
Stepwise model selection is also frowned upon, it's especially problematic when you use p-values / significance as the criteria instead of a measure that penalizes more complicated models like AIC or BIC.
If you really want to break out the 7th cruise as its own variable the way is to create a dummy variable:
mps$CRUISE7 = ifelse(as.numeric(mps$CRUISE) == 7, 1, 0)

Then you can use it like any other variable. But at this point you'll have trouble with the non-broken-out CRUISE variable, you'll probably need to break it out into each of their individual levels (see tidyr::spread) and then treat them all individually... well, all but one level which will be your reference and gets lumped in with the intercept (thanks to commenters!); inadvisable but not impossible. The standard approach would be to not break out the individual cruises.
