# Prediction when survey subsets create dramatically smaller Ns

Suppose you want to predict an outcome using a sample whose N is...

• 10,000 based on most demographic variables
• 9,000 based on Survey Question 1
• 3,000 who answered "Yes" to Question 1 and thus were given Question 1A
• 700 who answered "Yes" to Question 1A and thus were given Question 1B
• 4,000 who answered "Yes" to Question 2 and thus were given Question 2A
• 600 who answered "Yes" to Question 2A and thus were given Question 2B

What methods, if any, have you found that are successful/worthwhile/practical ways of pulling all such information into a single model?

• How is the "outcome" related to these subsets? – whuber Oct 10 '14 at 0:44
• Every person has a Y value. – rolando2 Oct 10 '14 at 0:46

If I understand your question correctly, there are 2 challenges in your data

1. 1000 missing value for question 1. There is a whole literature on how to handle missing values in regression. Statistical Analysis with Missing Data by Little and Rubin is a very good reference for this topic. I think this is a minor issue for you.

2. conditional branching in survey design. I think this is your main problem. I am not sure if there is any statistical model that can handle this. What I usually do in practice is to combine multiple questions. For example, suppose your outcome $Y$ is a numerical scale of depression level and you have the following questions: