Learn More about Weighting in Displayr

Weights in Displayr - General Resources

These are the best places to start to learn about weighting in Displayr.

• For a general overview of weighting tools in Displayr, start here: Technical Documentation: Weights in Displayr
• Our weighting ebook goes into more detail both on the theory and process of weighting in general and how to build weights in Displayr: How to Weight Survey Data
• This post shows how to merge multiple weights, such as wave or geography/market based weights: Creating and Working with JavaScript Variables

These resources address specific aspects of working with weights

• Technical Documentation: Managing Filters and Weights
• Technical Documentation: Weight Calibration
• The Correct Treatment of Sampling Weights in Statistical Tests

From here, the resources below dig into more specific aspects and uses of weights.

Effective Sample Size

• What is Effective Sample Size?
• Technical Documentation: Design Effects and Effective Sample Size

Unique Uses for Weight Variables

• How to Create a Bump Chart (Ranking Plot) from a Table Using Displayr
• Technical Documentation: Writing Functions for the flip Project R Package

Shapley Regression and Johnson's Relative Weights

Johnson's Relative Weights isn't about weighting survey data, but the technique will come up in results when looking for information about weighting on our blog or in our technical documentation. The collected resources on this topic are below.

• You Can Now Run Shapley Regression in Displayr
• The Difference Between Shapley Regression and Relative Weights
• Comparing Partial Least Squares to Johnson’s Relative Weights
• When to Use Relative Weights Over Shapley