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Loading, merging and analysing demographic and health surveys using R

International Journal of Public Health volume 59, pages 415–422 (2014)Cite this article

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Fig. 1

Notes

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

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

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

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

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

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

  7. 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.

  8. 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.

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Acknowledgments

We thank the anonymous reviewers for their insightful comments on an earlier version of the manuscript.

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Authors and Affiliations

  1. Department of Environment, Technology and Technology Management, Faculty of Applied Economics, University Antwerp, Prinsstraat 13, 2000, Antwerpen, Belgium

    Dieter Vanderelst

  2. Faculté de santé publique, Université catholique de Louvain, Clos Chapelle-aux-champs 30, 1200, Woluwe-Saint-Lambert, Belgium

    Niko Speybroeck

Authors
  1. Dieter Vanderelst
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  2. Niko Speybroeck
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Correspondence to Dieter Vanderelst.

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Vanderelst, D., Speybroeck, N. Loading, merging and analysing demographic and health surveys using R. Int J Public Health 59, 415–422 (2014). https://doi.org/10.1007/s00038-013-0538-2

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Keywords

  • Health Facility
  • Child Mortality
  • Poor Household
  • Wealth Index
  • Data Frame