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Level 1: Patient Level 2: Clinician Level 3: Hospital The design effect is larger than 2.0 for some items at Level 2 and is larger than 2.0 for nearly all items at Level 3. I am only interested in looking at Level 1 while correcting the SE's/chi-2 for the non-independence associated with Levels 2 and 3. "TYPE=TWOLEVEL COMPLEX" isn't really an option as this would force me to use a saturated Level 2 model and I wish to avoid this. Is there any other flexibility within Mplus to deal with this? |
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If you are only interested in looking at Level 1 while correcting the SE's/chi-2 for the non-independence associated with Levels 2 and 3 all you need to do is TYPE=COMPLEX; cluster=Clinician; There is no penalty for ignoring Hospital (that would matter only if you are making inference on the Clinician level) |
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Thanks Tihomir, I think some simulation evidence suggests ignoring a 3rd level could be problematic for level 1 bias but I can't be sure of this... could clinician and hospital be controlled by combining these two ID's together such as DEFINE: NEW_ID = Clinician_ID + Hospital_ID; TYPE = COMPLEX; cluster = NEW_ID; which would reflect the unique combination of clinician and hospital? |
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I assumed you have unique Clinician_ID, if you don't you need to make sure you do, possibly with the command you suggest. Actually I was incorrect in the previous message and indeed you are correct. It easy easy to see that if you consider the case where var on the second level is zero(the number of independent units will be number of hospitals and not number of clinicians). The Hospital variable should be ignored only if its ICC is small otherwise the SE will be incorrect. In fact the best practical thing to do is probably ignore the level (level 2 or 3) with smaller ICC. I can't think of an Mplus method that will give you what you want except "TYPE=TWOLEVEL COMPLEX". |
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shonnslc posted on Tuesday, August 27, 2019 - 9:02 am
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Hi, My data have three levels: 1st level: pre-service teachers 2nd level: programs/departments 3rd level: schools Since programs/departments are the same across schools (English, Social Science, Math, and Science), can I multiply 2nd and 3rd levels units to create unique 2nd level clusters? Then, I can use type = complex cluster = new2ndlevelunits (i.e., 2nd level units*3rd level units) Thanks! |
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This question is suitable for Multilevelnet or SEMNET. |
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