# Survey Weights: A Step-by-Step Guide to Calculation

Survey Weights: A Step-by-Step Guide to Calculation, by Richard Valliant and Jill Dever, is an excellent reference for survey data analysts and researchers. This book details the reasons for weighting and shows how to perform different weight-adjustment methods in Stata.

Topics covered include nonresponse, weight adjustment and calibration, linearized and replication-based variance estimation, multiple weights, two-phase sampling, composite estimation, and quality control when computing your own survey weights.

The authors assume familiarity with Stata and some applied sampling experience and knowledge of “lite” theory, such as the concepts of with-replacement versus without-replacement sampling and single- versus multistage designs.

List of figures

Preface (PDF)

Glossary of acronyms

1 Overview of weighting
1.1 Reasons for weighting
1.2 Probability sampling versus nonprobability sampling
1.3 Theories of population inference
1.4 Techniques used in probability sampling
1.5 Weighting versus imputation
1.6 Disposition codes
1.7 Flowchart of the weighting steps

2 Initial steps in weighting probability samples
2.1 Base weights

3.3 Tree-based algorithms

3.3.1 Classification and regression trees
3.3.2 Random forests
3.3.3 Boosting

3.4 Nonresponse in multistage designs

4 Calibration and other uses of auxiliary data in weighting
4.1 Poststratified estimators
4.2 Raking estimators
4.3 More general calibration estimation
4.4 Calibration to sample estimates
4.5 Weight variability

5 Use of weights in variance estimation
5.1 Exact formulas
5.2 The with-replacement workaround
5.3 Linearization variances
5.4 Replication variances

5.4.1 Jackknife
5.4.2 Balanced repeated replication
5.4.3 Bootstrap
5.4.4 Grouping PSUs to form replicates

5.5 Effects of multiple weight adjustments

6 Nonprobability samples
6.1 Volunteer web surveys
6.2 Weighting nonprobability samples
6.3 Variance estimation for nonprobability surveys
6.4 Bayesian approaches

7 Weighting for some special cases
7.1 Normalized weights
7.2 Multiple weights
7.3 Two-phase sampling
7.4 Composite weights
7.5 Masked strata and PSU IDs
7.6 Use of weights in fitting models

7.6.1 Comparing weighted and unweighted model fits
7.6.2 Testing whether to use weights

8 Quality of survey weights
8.1 Design and planning stage
8.2 Base weights
8.3 Data editing and file preparation
8.4 Models for nonresponse and calibration
8.5 Calibration totals
8.6 Weighting checks
8.7 Analytic checks
8.8 Analysis file and documentation

References