Dear user,

Thanks for your question, since you are wanting to examine parasitemia you should be using the PR file since this file includes all household members (not just kids whose mothers were interviewed). You can learn more about DHS data files in the following YouTube video https://www.youtube.com/watch?v=fzLNQkkvDeI&index=7& list=PLagqLv-gqpTNBR0KcyrajAqKrFdsdIqqe

To match Kenya MIS malaria table 6.2 it is important to look at the table description. Unlike other countries, Kenya MIS sampled children 6 months to 14 years. In most DHS surveys we only sample children 6 months to 5 years old. Because of this difference country specific age variables were created for Kenya. Country specific variables always start with the letter "s"

use KEPR7AFL.dta, clear gen micmalpos=0 replace micmalpos=(hml32==1) lab var micmalpos "Parasitemia (via microscopy)" gen rdtmalpos=0 replace rdtmalpos=(hml35==1) lab var rdtmalpos "Parasitemia (via RDT) " * Proportion of children 6 months to 14 years with malaria infection (RDT) tab rdtmalpos if shml16a>=6 & shml16a<=179 & hv103==1 & hml33==0 & hml35!=6 [iweight=wgt] * Proportion of children 6 months to 14 years with malaria infection (microscopy) tab micmalpos if shml16a>=6 & shml16a<=179 & hv103==1 & (hml32==0|hml32==1) [iweight=wgt]

I don't use SPSS, but here is some Stata code that may help. Yes, you must restrict to births in the last two years. This indicator also requires using 7 separate variables to construct it. You must combine responses from women who delivered in a facility and women who delivered at home, or who had a PNC check after returning home from the facility. You must also consider the provider of PNC when calculating this indicator.

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I am working on the Kenya Malaria Indicator Survey of 2015. First, how does one uniquely identify children in the data? And secondly, trying to replicate the results of Table 6.2, but getting a figure of 9058 by RDT and 9074 by microscopy. These are weighted. Please help. ]]>

I have selected (b19 < 24) to restrict my analysis to women who gave birth in the last two years before the survey but my results didn't match those that are in the 2015-2016 report. I found that 43.4% of women who gave birth in the last two years had a postnatal check during the first 2 days instead of 42.4% which is in the report. Is it that the figure in the report is not correct or my calculations are wrong?

Please also help me on how to manage missing values in this variable? I am trying to replicate the results on column 10 in the table 9.9 in the report.

Any suggestions will be greatly appreciated. Thank you

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I have selected (b19 < 24) to restrict my analysis to women who gave birth in the last two years before the survey but my results didn't match those that are in the 2015-2016 report. I found that 43.4% of women who gave birth in the last two years had a postnatal check during the first 2 days instead of 42.4% which is in the report. Is it that the figure in the report is not correct or my calculations are wrong?

Please also help me on how to manage missing values in this variable? I am trying to replicate the results on column 10 in the table 9.9 in the report.

Any suggestions will be greatly appreciated. Thank you

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I assume that you are using the children in the KR file. In that file, the mothers are identified by v001 v002 v003. I suggest the following:

egen mother_id=group(v001 v002 v003)

gen rn=uniform()

sort mother_id rn

egen sequence=seq(), by(mother_id)

keep if sequence==1

drop rn sequence

This procedure sorts the children of each woman in a random order, and then selects the child with the smallest random number. Because of the random step in it, the results will not be replicable, at least not exactly. Every time you run it, you will get a slightly different sample of children. That's inevitable if you do it at random An alternative would be to use all children, with a multi-level adjustment for the similarity of children of the same mother. Another alternative would be to take just the youngest child, for example, the child with bidx=1. However, that will introduce some bias (see https://www.dhsprogram.com/pubs/pdf/MR14/MR14.pdf).

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I am an undergraduate student investigating the association between women's decision-making variables (participation in decisions regarding spending income, her healthcare, major household purchases, visits to family and relatives) and stunting and wasting in her children under five. I am using the 2013-14 Democratic Republic of the Congo DHS.

I already created dichotomous variables for "Stunting Status" where HAZ< -2 SD and "Wasting Status" where WHZ < -2 SD according to WHO child growth standards. I currently have the child data set with linked mothers, but the problem is that the mothers are duplicated if they have several children (ex if a mother has 6 children, her data is counted 6 times). Now, I would like to randomly select one child per mother to create "mother-child pairs." Specifically, I would like to classify a mother-child pair as "exposed/malnourished" if the mother has at least one child who is stunted/wasted. How would I do this?

Thanks! ]]>

Kindly asking for the stata code for deriving the mean, median as shown in Table 5.6 for the Uganda 2016 udhs. I have used the code above and the figures match though less by a few decimal points. However, the code stops on deriving the totals and not the mean and median.

Any assistance is highly rendered. ]]>

Is this question about a specific survey, such as the NFHS-4 (India)? Are these sub-national regions, such as the states of India, or regions such as South Asia? Are you using Stata? It is not necessary to use logistic regression to calculate means of sub-groups. Please be more specific.]]>