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 Joshua Adams posted on Monday, October 12, 2015 - 11:10 am
Dear Drs. Muthen,

I had a question regarding changes in parameter estimates between single and multilevel models. Based on LR tests, a 3-level model was appropriate for my data. I compared four experimental conditions (level-2 in this case) using dummy coding. After observing a large discrepancy between the parameter estimates and basic descriptive statistics, I ran a single level model to confirm I coded correctly, which I did, and a two level model for diagnostic purposes. I observed marked parameter changes each time a level was added. Iíve found the same effect with several continuous metrics I was examining as well.

The number of cases within each level-2 cluster varies considerably. I am not sure if that would affect anything.

I was hoping someone could help me diagnose this issue.

Thank you
 Bengt O. Muthen posted on Monday, October 12, 2015 - 6:05 pm
Adding levels in multilevel analysis can very well change parameter estimates; that is to be expected. Your test says that the 1-level and 2-level models are wrong so their results should be ignored. The multilevel literature discusses these changes in estimates.

Varying number of cases within level 2 clusters should not be a major factor in what you are seeing.
 Joshua Adams posted on Tuesday, October 13, 2015 - 11:07 am
Dear Drs. Muthen,

I was expecting more conservative p-values, rather than a marked change in the estimates themselves, so I was concerned.

I appreciate the clarification.

Sincerely,

Joshua
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