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Support #1696

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random effects logistic regression models and weighting

Added by Zohra Ansari-Thomas over 2 years ago. Updated about 1 year ago.

Status:
Resolved
Priority:
Normal
Category:
-
Start date:
05/09/2022
% Done:

100%


Description

Hello,

I am attempting to run a random effects logistic regression model using waves 1-10 of the UKHLS, and am running into some issues with how to take into account the longitudinal weighting, strata, psu, as well as clustering by PIDP or allowing for random intercepts by PIDP to account for the longitudinal design of the study. I am using Stata

I can svy set my data to account for the longitudinal weights (indinus_lw), the psu, and the strata, but I am not sure how to account for the clustering by PIDP. I am using the svy: melogit command.

Any advice would be much appreciated, thank you!

Actions #1

Updated by Understanding Society User Support Team over 2 years ago

  • Status changed from New to In Progress
  • Assignee set to Olena Kaminska
  • % Done changed from 0 to 10
  • Private changed from Yes to No

Many thanks for your enquiry. The Understanding Society team is looking into it and we will get back to you as soon as we can.

We aim to respond to simple queries within 48 hours and more complex issues within 7 working days.

Best wishes,
Understanding Society User Support Team

Actions #2

Updated by Olena Kaminska over 2 years ago

Dear Zohra,

In multilevel modelling you can have a few levels, the highest of which will be PSU as a clustering variable, and you can use individuals at a lower level.

Hope this helps,
Olena

Actions #3

Updated by Understanding Society User Support Team over 2 years ago

  • Status changed from In Progress to Feedback
  • % Done changed from 10 to 80
Actions #4

Updated by Understanding Society User Support Team about 1 year ago

  • Status changed from Feedback to Resolved
  • % Done changed from 80 to 100
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