Inequality Analysis Using R: Disaggregated Data from Surveys (WHO)

For many countries, data from household health surveys are the main source of information for health inequality monitoring because they include data on both health indicators and dimensions of inequality. Yet, there are several considerations, including sampling design complexities and data quality, that must be taken into consideration when analysing and reporting disaggregated survey data.

The aim of this course is to provide learners with a practical guide to the preparation of disaggregated data sourced from household surveys using the statistical software R and RStudio. These data can then be used to monitor and analyse health inequalities using the WHO Health Equity Assessment Toolkit (HEAT Plus) software. The course offers an overview of the main considerations for the analysis of complex survey data and introduces learners to a set of R functions for disaggregated data preparation. The use of R code is demonstrated through examples using a sample dataset. The target audience is monitoring and evaluation officers, data analysts and other technical officers with an interest in data analysis. The course may also be of interest to students and researchers.

Course duration: Approximately 2 hours.

Certificates: A Certificate of Achievement will be available to participants who score at least 80% of the total points available in the final assessment. Participants who receive a certificate of achievement can also download an Open Badge for this course. Click here to learn how.