I am working on a multilevel analysis and I am interested in the group-specific betas. So I had the idea to save the group-level residuals. As far as I read in some above posted threads this was not possible in earlier versions of Mplus. Is this still true of Mplus 5.2 (5.21)?
i am running twolevel-regression-models w/ manifest variables using the complex option. i've been wondering whether it is possible to check for model assumptions (i. e. normality of residuals) while or after running the analyses? if so, could you please let me know how this can be done? is there a way to save level 1- and level 2-residuals?
i realize my questions are kind of naive and i apologize - i'm only getting started working with mplus.
since my last post, i've come to realize that it's actually the "twolevel"-option i'm using in my analyses.
am i using the mlr estimator all the same and how about the fiml algorithm? i was told it was working automatically if i wrote nothing but "type = twolevel" in my analysis-command. is that true? the reason i'm asking is that i get the following warning:
*** WARNING Data set contains cases with missing on x-variables. These cases were not included in the analysis. Number of cases with missing on x-variables: 20 1 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS
I get a similar warning concerning the dependent variable.
is fiml replacing the missing values still or are they in fact excluded?
again - sorry to bother you if this seems all too stupid to ask.
Observations with missing values on the observed exogenous variables in the model are excluded because the model is estimated conditioned on these variables. Missing data theory applies only to observed endogenous variables. If you want the observations with missing on the observed exogenous variables to be included, mention their variances in the MODEL command. They will then be treated as endogenous variables and distributional assumptions will be made about them. Observations will missing on all dependent variables are also excluded because they contribute no information.
i'm sorry, but i still don't seem to understand. it's a multilevel regression model with manifest variables and i'm not specifying anything but "type = twolevel" in the model command. in this case - am i using mlr (because it's the default) and is fiml operating, too although i get the warning menttioned above, that variables with missings on x-variables are excluded from the analysis? i mean are they estimated by fiml despite the warning or are they really not included?
thank you very much for your answer! but why is it that i don't find fiml in the "twolevel"-section of the "estimator"-list in the user's guide (p. 483)?
i still don't seem to get that straight: with type = twolevel and nothing else changed - am i using mlr as stated in the user's guide or am i using fiml? or are they in fact the same? where can i find a reference to better understand what fiml is doing? how can i best describe to a reader how my models are being estimated?
The current Version 6 user's guide has the information on page 532. The estimators ML, MLR, and MLF are full-infomration maximum likelihood estimators (FIML). See the Little and Rubin book on the reference list in the user's guide for a description of how Mplus handles missing data estimation.
Yes. With categorical outcomes and maximum likelihood estimation, some models require numerical integration. This is computationally very demanding. There is a brief description of this in the user's guide.
Do I understand correctly that MPlus version 7 does not allow analysts to save the level 2 residuals?
This is especially an issue for multilevel logistic regression. Researchers argue that average marginal effects is the best way to convey effects in a logistic regression. My understanding is that in a multilevel context to calculate AMEs the level 2-specific intercept needs to be included to calculate each case's predicted probability.