I have a dataset with 101 observations and 402 columns (those columns comprise several multiple-item questionnaires). Among those 402 columns, 10 of them are categorical and the remaining are continuous. There are 82 observations without missing values, which means 18% of the entire sample (N=101) has one or more missing values. There are 14 missing patterns with 10 of them containing only one observation.
I would like to examine if the missing data mechanism is MCAR in this dataset. I have tried LittleMCAR ("BaylorEdPsych" package) and TestMCARNormality ("MissMech" package) to test for MCAR using RStudio (version 1.1.442). However, LittleMCAR only allows a maximum of 50 variables; TestMCARNormality did not work out either. The code for TestMCARNormality is shown as below:
## df[1:10] were excluded due to their class of categorical variables; del.lesscases was set to 1 because default for this parameter was 6, and if set to default it would have no missing pattern in the test.
TestMCARNormality(df[11:402], del.lesscases = 1)
After I ran this code, it showed the following error:
Error in solve.default(sigoo) : system is computationally singular: reciprocal condition number = 1.37693e-17
I wasn't sure why this happen and what it meant. I was wondering if anyone knows how I can address this issue and how I can test MCAR for my dataset. Thank you in advance for your time; sincerely appreciated!!