zero coefficient added for missing dummy var

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gilleecl
Posts: 23
Joined: Fri Dec 17, 2010 11:24 am

zero coefficient added for missing dummy var

Post by gilleecl » Tue Aug 29, 2017 8:28 am

Hi,
I have set missing values on all variables in my dataset to be 99. My model contains some categorical variables. As an example, I have a binary variable with yes/no responses and reference category 'yes' but the model is adding a parameter estimate and standard error (both zero) for 'omitted or invalid' for this variable. (This happens sometimes even when there are no missing data on a variable).

Example:
ReadScoreij = B0j - 34.461(6.669)Noij + 0.000(0.000)Omitted or invalidij + eij.

Can I safely ignore the "omitted or invalid" parameter estimate and standard error (as missing data are dealt with using Realcom Impute) and proceed to use a t-test (or intervals and tests when two or more dummy vars) to determine significance? If MlwiN adds n dummies including one for 'omitted or invalid', is it reasonable to assess significance on the basis of n-1 functions in intervals and tests?

Many thanks
Lorraine

ChrisCharlton
Posts: 890
Joined: Mon Oct 19, 2009 10:34 am

Re: zero coefficient added for missing dummy var

Post by ChrisCharlton » Tue Aug 29, 2017 4:36 pm

When MLwiN creates dummy variables it does so on the basis of the category labels assigned to the variable, whether or not there are any underlying data points corresponding to these. I would suggest using the Regenerate button on the variable in the names window, which will remove any categories that have no data as well as create extra categories if there are values with no existing labels.

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