st: Missing Values in Multiple Imputation Data Sets

[Patti Fritz <pfritz@uwindsor.ca>]

Hello All,

I am a novice to Stata, having just begun using it 3 weeks ago. Therefore, my questions are likely very naive. I am trying to conduct multiple imputation of a data set that primarily contains positively skewed/frequently over-dispersed ordinal predictor variables (i.e., history of various forms of family-of-origin aggression assessed on 3- or 4-point scales from not at all to a lot); my other predictors consist of demographic variables (e.g., age, gender, income, number of marriages, marital status). My outcome variables are dichotomous (partner violence) and the sample size is N = 3,635. There is substantial missing data on some of the items (e.g., 21%), and complete data across all variables is only found among 556 cases). When I attempt to conduct mi impute chained commands (I've tried poisson, and nbreg), there are still some missing values in some of the imputed data sets. Specifically, every variable still has some missing data across the 20 imputed data sets. Is there!
  a way to alleviate this problem? 

I can get the mi impute mvn command to work, but after reading some of the literature, I'm not sure this is the best approach. In addition, I haven't been able to get the mi chained (ologit) command to work because I get the following error: 

matsize too small
    You have attempted to create a matrix with too many rows or columns or attempted to fit a
    model with too many variables.  You need to increase matsize; it is currently 800.  Use set
    matsize; see help matsize.

    If you are using factor variables and included an interaction that has lots of missing
    cells, either increase matsize or set emptycells drop to reduce the required matrix size;
    see help set emptycells.

    If you are using factor variables, you might have accidentally treated a continuous variable
    as a categorical, resulting in lots of categories.  Use the c. operator on such variables.
error occurred during imputation of g2sabuse_s05 ipvabuse_s05 s2gabuse
_g04 ipvabuse_g04
f2sslap_s94 m2sslap_s94 f2gslap_s94 m2gslap_s94 s2gslap_s94 g2sslap_s94 p2pslap_s94 f2sslap_s05
f2sabuse_s05 m2sslap_s05 m2sabuse_s05 f2gslap_g04 f2gabuse_g04 cp260hec cb103redr gb103redr on m
= 1
r(908);

I only have Stata/IC 12.1 on my laptop, but I'm going to see if the computer labs at work have the SE version. If yes, I'll see if I can get the ologit command to work. Regardless, I'm interested in finding out why missing values are found in the imputed data sets.

Thanks in advance for your time and assistance. They are greatly appreciated!

Cheers,

Patti



Patti A. Timmons Fritz, Ph.D., C. Psych.
Associate Professor
Department of Psychology
University of Windsor
Windsor, Ontario N9B 3P4
Canada

 

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