| Pooling data & DV weights [message #17861] |
Thu, 27 June 2019 16:31  |
12345Ap
Messages: 1
Registered: June 2019
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Hi,
I am analyzing domestic violence experiences among women in Kenya, Tanzania, and Uganda. These three countries were chosen for practical and theoretical reasons. The goal is to profile DV experiences among women in this region using latent class analysis. I will be running the latent class analysis for all three countries combined, differential item function will assess the potential differences in item responses for each of the DV items by country and if necessary paths will be fixed, and then the latent class model will be run for each of the countries separately to examine if the same or close to same profile of DV emerges in all four scenarios. If this is the case and the initial latent class model is replicated across countries, I will also be adding covariates in the merged country model to 1) assess whether the same profile of DV continues to emerge even with the addition of covariates (socio-demographics, characteristics known to be related to DV items, and country of residence to account for further differences by country), and 2) to assess whether covariates are related deferentially to the different DV types or classes. I have some questions about weights that are somewhat unclear.
1) For basic descriptive statistics and crosstabs - I should be de-normalizing the weight to account for sample size differences correct? Would it ever make sense not to do this and just to use the original DV weight recognizing that the larger country is going to pull the frequencies/descriptive stats?
2) When running the latent class model if I use the regular DV weight and then include country as a covariate, doesn't this essentially account for potential biases based on the country (and different N sizes), and negate the need to use a de-normalized DV weight?
Thanks, I'm struggling to grasp some of the issues around weights.
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