Message/Author 

Anonymous posted on Wednesday, September 21, 2005  7:02 am



I have a question about using weights in a multilevel SEM model. This model has two latent variables and six oberved at level2 and the same setup at level1 with different variables. Because of this and the data are clustered, I wanted to use multilevel SEM analysis. Also, the data come with weights. How would I incorporate the weights into my model? Is there an example in the manual that I am overlooking? Thank you in advance for your assistance 


You would use the WEIGHTS option of the VARIABLE command to specify which variable contains the sampling weight information. 

Anonymous posted on Wednesday, September 21, 2005  2:33 pm



I'll give it a try. 


Hi, I am using data from a national survey. A bootstrapping procedure was used to create 500 sets of sampling weights which have been provided by the owner of the database for the purpose of estimating standard errors while taking the survey design into account. Is there a way in MPlus to combine model estimates based on these sampling weights or do I have to manually run the models 500 times and then manually calculate the stardand errors based on the distributions of the obtained estimates? 


If you have 500 data sets each with a different weight, you can use external Monte Carlo (Example 11.6, Step 2) to analyze them. You will obtain results that are the average parameter estimates, the average standard error, etc. (see Chapter 11, Monte Carlo Output. I'm not sure this is exactly how these replicate weights should be used. 


Hi, I'm using the European Social Survey data which has two sampling weight variables (a Design weight to control for not all people being given the same chance of selesction, and a population weight to accurately represent country populations). I am testing a twolevel model (country level and individual level). I'm wondering how I include both weight variables. Do I say WEIGHT = DWEIGHT PWEIGHT Thanks for your help 


For the twolevel model you should use only WEIGHT = DWEIGHT, however if you want to estimate population totals you should use single level models with weight the product of DWEIGHT and PWEIGHT. 


Do you know any reference explaining why we should not use pweight in a twolevel sem model? Many thanks 


You should construct your weights so that the level 2 weight is 1 / Prob of including that cluster in the sample and the level 1 weight is 1 / Prob of including the observation in the sample. See http://statmodel.com/download/asparouhovgmms.pdf 


We are trying to estimate a latent class growth analysis using Add Health data, and we are therefore applying complex sampling weights. Importantly, we are using a subsample of the full data (i.e., only 7th graders). We used Type=Complex TwoLevel and included wtscale=ecluster to try to accommodate for using only a portion of the full data. However, we only wish to specify a withingroup model, and the results of the twolevel model were uninterpretable. [All individuals were assigned to a single group even though three groups were specified.] Can we use Type=Complex (without TwoLevel) and incorporate some other method of adjusting the weights to account for use of a subpopulation? 


You can use the SUBPOPULATION option with TYPE=COMPLEX. 

Back to top 