Analyzing data from sample surveys
A sample survey is conducted to obtain information about the characteristics of a population. To reduce the cost and time necessary to collect the data, this task is often handled by selecting a subset (a sample) from the target population of interest to the researchers. The sample design adds certain characteristics to the data that may bias the analysis. The general term for this potential bias is the "sample survey design effect." Methods are available to adjust the analysis to account for some of these characteristics. There should be variables for each observation in your data set to identify each of the characteristics that are described next.
Stata has a well-developed and straightforward set of commands that allow you to adjust your analysis for the sample survey design effect. This section of the tutorial discusses how to use these survey data commands. The discussion is divided into:
- Data Characteristics
- Choosing the Correct Weight Syntax
- Commands to Analyze Survey Data
- Logistic Regression Analysis
- Common Errors and How to Avoid Them
Most of the information in this section on analyzing survey data was provided by Kim Chantala. However, please direct questions and comments to Phil Bardsley as noted below.