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weighting child data [message #13756] Tue, 19 December 2017 16:18 Go to next message
slolib86 is currently offline  slolib86
Messages: 2
Registered: December 2017
Location: Peru
Member
Dear all,

I going to investigate factors associated with child height (zscore variable). My main concern is about weights. I read in other messages of the forum, that we have to weight the child data (krfile) using the v005 variable. However, the v005 variable comes from the mother data (irfile) where all the data is unique per caseid variable.

I would like to know if there any problem weighting the child data(krfile) since some values of the v005 variable are repeated per caseid.

Thank you so much for your response
Re: weighting child data [message #13776 is a reply to message #13756] Thu, 21 December 2017 09:59 Go to previous messageGo to next message
Liz-DHS
Messages: 1123
Registered: February 2013
Senior Member
A response from senior sampling expert, Dr. Ruilin Ren:
Quote:

Regarding the weight variable used for analyzing the child weight, it is depending on the background. If you take only the children living with an interviewed mother, it is better to use the variable V005, the child's mother's weight. If you take all children measured in the household, it is better to use the household weight HV005. Regarding the repeated values of the weight variable (either HV005 or V005), note that the weight is a cluster level weight in DHS surveys, all HH in the same cluster share the same weight; all women in the same cluster share the same weight. So this is not a concern.
Thanks
Ruilin

Re: weighting child data [message #13845 is a reply to message #13776] Thu, 11 January 2018 14:31 Go to previous messageGo to next message
slolib86 is currently offline  slolib86
Messages: 2
Registered: December 2017
Location: Peru
Member
Thank you for your response Dr. Ruilin Ren

I have two more questions regarding weights. I am pooling DHS surveys , two surveys per country. The country I selected is Perú. I read that before to run a regression model, I should re-normalize the weights.

I proceed like previous post suggestion:

V005*=V005×(total females age 15-49 in the country at the time of the survey)/(number of women age 15-49 interviewed in the survey)

Since my outcome is child weight:

(1) Could I re-normalize the weigths using this conversion factor?

V005*=V005×(total children age 0-5 in the country at the time of the survey)/(number of children age 0-5 interviewed in the survey)

(2) is there other way to re-normalize the weight that you could suggest to me?


Thank you so much
Re: weighting child data [message #13865 is a reply to message #13845] Tue, 16 January 2018 08:03 Go to previous messageGo to next message
Oquendo is currently offline  Oquendo
Messages: 1
Registered: January 2018
Member
We're also in the middle of a project in which we need to account for weight renormalization. No one on our team is sure how to do this. If anyone knows the best way to do this, we would appreciate it a lot. Thank you.
Re: weighting child data [message #13869 is a reply to message #13845] Tue, 16 January 2018 12:31 Go to previous message
Liz-DHS
Messages: 1123
Registered: February 2013
Senior Member
A response from senior sampler, Dr. Ruilin Ren:
Quote:

For Q#1: The answer is no. The "re-normalize" (rather d-normalize in our words) is to reverse the normalization procedure, so it has to use the women population size and sample size. The children's population size and sample size were not used in the weight normalization.

For Q#2: The answer is no. As stated in the question above, "re-normalization" is to remove the normalization factor from the normalized weight, there is no other way. But if you pool different survey data from the same country, you can "re-normalize" the weight using number of households to approximate, this assumes that the average number of women 15-49 per household is constant across surveys.

V005*=V005×(total number of residential households in the country at the time of the survey)/(number of households interviewed in the survey)

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