| Trends in vaccination coverage and factors for complete vaccination [message #19678] |
Thu, 30 July 2020 01:20  |
kiyolsakie6
Messages: 1
Registered: July 2020
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Member |
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Hi,
Which method can I use to determine the trends in vaccination coverage of the six vaccines for a country such as Nigeria, using its 2006 and 2013 DHS datasets?
How can i build the multivariable logistic regression model to determine the factors associated with complete vaccination in nigeria using the 2013 dataset?
How can i determine the risk factors for Under- or non-immunization using the same dataset?
I am using stata for my analysis and I am looking at vaccination coverage in children aged 12-23 months.
[Updated on: Fri, 31 July 2020 07:32] by Moderator Report message to a moderator |
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| Re: Trends in vaccination coverage and factors for complete vaccination [message #19697 is a reply to message #19678] |
Tue, 04 August 2020 09:51  |
Bridgette-DHS
Messages: 3208
Registered: February 2013
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Senior Member |
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Following is a response from DHS Research & Data Analysis Director, Tom Pullum:
For the first question, I recommend combining the two surveys into one file with "append", constructing a variable "survey" to identify which was which. The first survey could have survey=1 and the second survey would have survey=2. Then you would basically do exactly what you would do with just one survey, to see whether there is a difference between urban (v025=1) and rural (v025=2) areas. In Stata you would need to make the svyset and svy adjustments, which are described in other postings.
For the second and third questions, you would first look at the main reports on these surveys to see what covariates were used, and at publications using DHS data and other data. You are limited to variables in the data, so the list of candidate covariates (potential risk factors) is not very long. They include region, urban/rural residence, education of the mother, wealth quintile, etc. Cluster-level spatial covariates could be helpful. The process would not be very different from what you would do with any outcome.
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