Is it possible to use multiple imputed data in a principle component analysis if my data are not normally distributed? I found this helpful link: https://www.stata.com/support/faqs/s.../cmdok-option/ but I get the following errors because of my non-normally distributed data: Warning: variance matrix is nonsymmetric or highly singular and:
mi estimate: omitted terms vary. The set of omitted variables or categories is not consistent between m=1 and m=41; this is not allowed. To identify varying sets, you can use mi xeq to run the command on individual imputations or you can reissue the command with mi estimate, noisily r(498);
Here is my code:
mi estimate, cmdok noisily: pca OverallFallsRiskScore Dual_TUG NIA_TotalScore GDS shortFES VAS FCI MOCA TrailB_A Stroop3_2 DigitBackward DSST_n, vce(normal) mineigen(1) comp($ncomp) blanks(.3)
Thanks for your help!
Deb
Related Posts with Can I use multiple imputed data in a principle component analysis if my data are not normally distributed?
Tab output for stataHi, Just ran into something weird in stata. I have split a variable into three variables and have u…
Combining several smoothed plots into one paneI have longitudinal data and want to examine inter-individual differences in the within functional f…
from df and p-value to calculate the lower bound t scoreIs there a way to calculate the two-tail t-score from df and p-value without looking up in the t-tab…
control variables difference-in-differenceHi there, I was wondering about adding control variables to a DiD model. I'm following instructions…
Need help with invalid synatxI'm trying to run a for loop which inputs extracts values from the rtable for a variable after runni…
Subscribe to:
Post Comments (Atom)
0 Response to Can I use multiple imputed data in a principle component analysis if my data are not normally distributed?
Post a Comment