Censored Two Level Model? PreviousNext
Mplus Discussion > Multilevel Data/Complex Sample >
 Anonymous posted on Sunday, August 07, 2005 - 7:31 am
I have data that is in a two level structure, children nested within families.

The variable of interest is latent with 3 indicators. The indicators are censored at the bottom (ie, zero inflated).

However, when I attempt to run the two level SEM model in Mplus, I get the following message:

*** ERROR in Analysis command
TYPE=TWOLEVEL is not available when outcomes are censored, unordered
categorical (nominal), or count variables.

So, may this be an error on my part in the model commands?

Or if not, could you offer a suggestion as to how to go about using the censored command while still taking into account the nesting structure of the data?

Thank you for your time.
 bmuthen posted on Monday, August 08, 2005 - 1:24 pm
No, not an error on your part. It is simply the case that the current Mplus version does not cover 2-level censored analysis. You can, however, use type=complex to correct your SEs for the nested data structure.
 Tashia Abry posted on Monday, September 29, 2014 - 11:24 am
Drs. Muthen,

I have noticed that in an analysis using a censored (from above) dependent variable , the adjusted mean for the outcome is slightly greater than the scale maximum. When running the exact same model without the Censored command, the adjusted mean is within scale limits leading me to believe the discrepancy is a function of censoring the DV. I would like to present the results from the Censored model, but wanted to make sure this was appropriate even though the adjusted mean is greater than the scale maximum. If so, how could we most accurately interpret the adjusted mean in the censored model?

Thank you.
 Bengt O. Muthen posted on Tuesday, September 30, 2014 - 8:40 am
Under the censored model the DV is y*, the latent continuous response variable underlying y. Because you have censoring from above, y* stretches beyond the max observed value and can therefore get a high y* mean. Please see the censored-normal literature, also mentioned in our Topic 2 handout and video.
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