Getting CIs Around Row Proportions with the Survey Package in Tech Support

Getting Ci Around Row Proportions with the CHIS Survey Package Tech Support

If you are working with survey data using a complex survey design such as the California Health Interview Survey (CHIS), and trying to calculate row proportions, you might have encountered some challenges. This article aims to help you navigate these challenges with the CHIS Survey Package Tech Support.

Context

svydesign function in R is commonly used for the analysis of complex survey data. This function takes into account the survey design components such as weights, clusters, and strata to provide more accurate estimates than simple random sampling. The CHIS survey package is an R package that provides an easy-to-use interface for analyzing CHIS data using the svydesign function.

Calculating Row Proportions

Calculating row proportions is a common task in data analysis that involves dividing the number of observations in a row by the total number of observations in the table. In the context of complex survey data, calculating row proportions is not as straightforward as dividing the number of observations in a row by the total number of observations. Instead, we need to take into account the survey design components.

Using the CHIS Survey Package

The CHIS Survey Package provides functions that enable the calculation of row proportions for complex survey data. To perform this task, we can use the row_prop function. This function takes a svydesign object and calculates the row proportions, taking into account the survey design components.

Example

Let's consider an example to illustrate the use of the row_prop function. Suppose we have a table of CHIS data that contains the number of males and females in different age groups.

# Load the CHIS Survey Package
library(chis.package)

# Read in the CHIS data
data(chis2019)

# Create a svydesign object
chis_design <- svydesign(id = ~psu, strata = ~strata, weights = ~wt, data = chis2019)

# Create a table of the data
table <- with(chis2019, table(sex, agegr))

# Calculate the row proportions
row_prop <- row_prop(table, design = chis_design)

Calculating row proportions for complex survey data such as CHIS data requires considering the survey design components such as weights, clusters, and strata. The CHIS Survey Package provides functions that enable the calculation of row proportions, taking into account these components. The row_prop function in the CHIS Survey Package takes a svydesign object and calculates the row proportions, providing accurate estimates for complex survey data.

References

• Lumley, T. (2010). Complex surveys: A guide to analysis using R. Chapman and Hall/CRC.
• Korn, E. L., & Graubard, B. I. (1999). Analysis of health surveys. John Wiley & Sons.
• CRAN Task View: Survey Sampling (https://cran.r-project.org/view=SurveyMethods).