Survey Design (SVY) for DHS

Understanding Key Variables in DHS Data: v005, v021, and v022

When working with Demographic and Health Surveys (DHS) data, it is crucial to understand certain standardized variables that are consistent across different countries and survey rounds. Three of these essential variables are v005, v021, and v022. These variables play a vital role in ensuring accurate and representative analysis of DHS data.

v005 - Sample Weight

The v005 variable represents the sample weight for each individual in the survey. It is a six-digit number with 6 implied decimal places. Sample weights are used to adjust for the probability of selection, non-response, and other adjustments to ensure that the survey results are representative of the entire population. When analyzing DHS data, it is crucial to use these sample weights to obtain unbiased and accurate estimates.

v021 - Primary Sampling Unit (PSU)

The v021 variable indicates the primary sampling unit or cluster number. In DHS surveys, households are often grouped into clusters known as PSUs. This variable helps in accounting for the survey's complex design by identifying these clusters. Properly accounting for PSUs is essential for accurate variance estimation and analysis.

v022 - Sample Stratum Number

The v022 variable represents the sample stratum number. Stratification is a technique used in survey sampling to divide the population into different subgroups, or strata, based on certain characteristics. In DHS surveys, strata are often formed by geographic regions and urban/rural areas. This variable is important for specifying the stratification in the survey design, which is critical for proper weighting and variance estimation.

Using DHS Variables in R

To effectively analyze DHS data, it is important to account for these variables in your statistical analysis. Here is an example of how to use these variables in R to set up

# Install and load the survey package
install.packages("survey")
library(survey)

# Assuming your DHS data is in a data frame called df
# Create a survey design object
dhs_design <- svydesign(
  id = ~v021,        # Primary Sampling Unit (PSU)
  strata = ~v022,    # Strata
  weights = ~v005,   # Sample weights
  data = df,
  nest = TRUE
)

# Now you can use the dhs_design object to perform weighted analyses

This setup allows you to correctly analyze the DHS data, taking into account the complex survey design, including clustering, stratification, and sampling weights.

Conclusion

Understanding the roles of v005, v021, and v022 in DHS data is essential for accurate and representative analysis. By properly incorporating these variables into your analysis, you can ensure that your findings are both valid and reliable. Whether you are a seasoned researcher or new to DHS data, mastering these key variables will significantly enhance the quality of your analysis.