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
louisecowpertw...@gmail.com
021 258 9795
Auckland, NZ
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