Hi there,

I have subscribed to R-help but am not sure how to view or post questions? I think this is the right way.

I am planning on doing a multivariate regression investigating the relationship between depression (a continuous variable) and social support variables (mostly continuous, some categorical) among older people. I have a number of demographic and health-related variables that I am including as control variables. I have a large dataset from nearly 4,000 individuals. 

I need to check whether my data is 1) Missing at Random (MAR) and 2) Missing Completely At Random (MCAR).

Here are three questions that I have related to this:


1) To check whether the data is MAR, I dichotomised a variable into missing and not missing, and checked for any significant differences in means (for continuous) or proportions (for categorical) of the other variables. I did this for each of the variables in my analysis. Is this correct?

2) Because of the size of my dataset, relationships for my MAR analysis are coming up as significant when, practically, the differences in means or proportions are not meaningful. Is it acceptable for me to argue as such, and say that the data is effectively MAR despite statistical significance?

Sorry this is not a question specifically to R (more of a stats question) so no problem if no-one can help, though it would be greatly appreciated.

3) I have no idea how to check whether the data is Missing Completely At Random in R. I think this involves seeing whether those who had missing data for one variable were more likely to have missing data in other variables? If so, I don't know how to do this. Or, I need to do an overall test like Little's test of missing completely at random. I have spent ages looking online and at packages and can't find anything.

Please help! I don't want to use SPSS!

Cheers,

Louise





Louise Cowpertwait
louisecowpertwait@gmail.com
021 258 9795 
Auckland, NZ




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