I have a meeting frequency variable and I want to determine whether it has an effect on hypothesized relationship, by 1) controlling for it and 2)examining whether it is a moderator. Unfortunately, it wasn't a very sensitive measure and distribution is skewed. The breakdown is: 10% daily, 5% twice a week, 52% weekly, 27% fortnightly and 6% monthly.
Someone suggested that because of the distribution (52% in a single category), I wouldn't get anything meaningful out of using it as a ordinal/likert variable. They said, instead, I should dichotomize it as weekly or more (67%) or less than weekly (33%).
I'm unclear on whether or not I should do this. The articles I have read on dichotomizing variables (e.g. MacCallum et al., 2002) say that it is only okay to dichotomize when "the distribution of a count variable is extremely highly skewed". Meeting frequency is skewed (standardised skewness = ~-2), but it is not extremely highly skewed.
Thoughts? I'm thinking at the moment, I'm better off treating it like a likert variable, and then in the limitations section of discussion saying that the variable had low variance and was not very sensitive and this limits the validity of the findings.
Any assistance on this would be great.
The article I read about this is: On the practice of dichotomization of quantitative variables. MacCallum, Robert C.; Zhang, Shaobo; Preacher, Kristopher J.; Rucker, Derek D. Psychological Methods, Vol 7(1), Mar 2002, 19-40