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01-04-2014 | Hints & Kinks

Loading, merging and analysing demographic and health surveys using R

Authors: Dieter Vanderelst, Niko Speybroeck

Published in: International Journal of Public Health | Issue 2/2014

Excerpt

The MEASURE DHS project collects nationally representative data on health and population. Typically, multiple surveys have been conducted for each country. To date (October 2013), the DHS website provides data from over 300 surveys conducted in more than 90 countries. This makes the DHS a very interesting data source. Needless to say, MDHS data have been used in a wide variety of studies (Van Malderen et al. 2013; Van de Poel and Speybroeck 2009; Masanja et al. 2008). The MEASURE DHS project maintains a database of survey-based publications.¹ …

Available only for authorised users

Database of DHS based publications: http://www.measuredhs.com/publications/index.cfm.

One very well-written hands-on tutorial can be found at http://personality-project.org/r/.

List of books on R: http://www.r-project.org/doc/bib/R-books.html.

The listing of all available DHS surveys: http://www.measuredhs.com/data/available-datasets.cfm.

DHS instructions on acessing the data http://www.measuredhs.com/data/Using-Datasets-for-Analysis.cfm.

DHS Recode Manuals: http://www.measuredhs.com/publications/publication-dhsg4-dhs-questionnaires-and-manuals.cfm.

Normally, one would use family=binomial to specify a logistic regression in R. However, as we are using weighted data, we need to use family=quasibinomial . Please refer to the survey package help on the svyglm() function for more details.

The coefficient denotes the log of the increase in odds ratio associtated with increasing the predictor by one unit. Hence, \(\Updelta \frac{p}{1-p} = {\rm e}^{0.158} = 1.172. \) Hence, odds ratio is predicted to increase by 1.17 for each increase in wealth index.

Konings P, Harper S, Lynch J, Hosseinpoor AR, Berkvens D, Lorant V, Geckova A, Speybroeck N (2010) Analysis of socioeconomic health inequalities using the concentration index. Int J Public Health 55(1):71–74PubMedCrossRef

Lumley T (2004) Analysis of complex survey samples. J Stat Softw 9(1):1–19

Lumley T (2013) Survey: analysis of complex survey samples, R package version 3.29-4

Lumley T (2011) Complex surveys: a guide to analysis using R, vol 565. John Wiley, London

Masanja H, de Savigny D, Smithson P, Schellenberg J, John T, Mbuya C, Upunda G, Boerma T, Victora C, Smith T et al (2008) Child survival gains in Tanzania: analysis of data from demographic and health surveys. Lancet 371(9620):1276–1283

Speybroeck N, Harper S, de Savigny D, Victora C (2012) Inequalities of health indicators for policy makers: six hints. Int J Public Health 57:859–860CrossRef

Speybroeck N, Konings P, Lynch J, Harper S, Berkvens D, Lorant V, Geckova A, Hosseinpoor AR (2010) Decomposing socioeconomic health inequalities. Int J Public Health 55(4):347–351PubMedCrossRef

Van de Poel E, Speybroeck N (2009) Decomposing malnutrition inequalities between scheduled castes and tribes and the remaining Indian population. Ethn Health 14(3):271–287CrossRef

Van Malderen C, Van Oyen H, Speybroeck N (2013) Contributing determinants of overall and wealth-related inequality in under-5 mortality in 13 African countries. J Epidemiol Commun Health 67:667–67CrossRef

Title: Loading, merging and analysing demographic and health surveys using R
Authors: Dieter Vanderelst
Niko Speybroeck
Publication date: 01-04-2014
Publisher: Springer Basel
Published in: International Journal of Public Health / Issue 2/2014
Print ISSN: 1661-8556
Electronic ISSN: 1661-8564
DOI: https://doi.org/10.1007/s00038-013-0538-2

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