| Weigthing and pooling multicountry datasets [message #24571] |
Thu, 02 June 2022 07:32  |
Denise_kpebo
Messages: 2
Registered: June 2022
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Member |
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Hi,
I am working on a multilevel logistic regression for multi-country (n=15) study using the DHS guide (https://www.dhsprogram.com/pubs/pdf/MR27/MR27.pdf) for the calculation of level weight.
Firstly, I have conducted the analysis within each country separately to determine which level of alpha should be used (e.g., allocation of variation in weights to the level-1 and level-2 units).
Then based on alpha for each country, I've weighted each dataset separately before merging the 15 countries datasets
Is this sufficient? May I start my analysis at this point with the pooled database using the svyset command?
Or do I still need to apply additional weights considering the differences in population size, since the population are not the same? And if so, how can I do that?
Many thanks in anticipation of your help
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| Re: Weigthing and pooling multicountry datasets [message #24581 is a reply to message #24571] |
Fri, 03 June 2022 08:45  |
Janet-DHS
Messages: 393
Registered: April 2022
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Senior Member |
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Following is response from DHS Research & Data Analysis Director, Tom Pullum:
There have many postings on how to weight pooled surveys. There are basically two options. The first is to re-scale the weight for each country so that the total weight for country X is proportional to the population of country X at the time of the survey. You can get the estimated population size from the UN Population Division website, World Population Prospects 2019. The second option is to rescale so that the total weight is the same for each country (or survey). That is, if you pool 10 countries, you re-scale so that each survey has 1/10 of the total weight. Specific steps for both options have been given on the forum.
The first option has the problem that typically one large country, such as India or Nigeria, will completely dominate the results.
At DHS we often leave the weights alone and pool surveys into a single file just to simplify the data processing. We give results separately for each survey, but do not give results for all the surveys combined. Pooled surveys, from different countries and different years, do not describe a well-defined population. It's very hard to interpret a mean or percentage or coefficient from a mix of different surveys.
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