Blocking in choice experiments

Using blocking within an experimental design to reduce respondent burden in a choice experiment.

A step-by-step interactive tutorial on blocking in choice experiments in SurveyEngine. Preview the live tutorial, then download and upload it to your account to examine the construction.

Ben White, 08.07.2026

What this tutorial covers

Using blocking within an experimental design to reduce respondent burden in a choice experiment.

Each page of the tutorial demonstrates a specific technique. Work through it as a respondent first, then open the editor to see how it was built.

What you will learn

After completing this tutorial you will be able to implement blocking in choice experiments in your own SurveyEngine surveys.

Download the tutorial ZIP and upload it to your account to use it as a starting point or template for your own work.

TLDR Quick links

Preview the live tutorial

Download the tutorial ZIP

Open a free account

Step-by-step walkthrough

Step 1: Understand why blocking is needed. A full D-efficient design may require more choice sets than any single respondent can complete.

Step 2: Set the number of blocks. Divide the full design into blocks of 6 to 10 choice sets each.

Step 3: Configure block assignment. SurveyEngine randomly assigns each respondent to a block so each sees only their subset of choice sets.

Step 4: Check within-block efficiency. Verify that each block has adequate D-efficiency for stable parameter estimation.

Step 5: Analyse across blocks. Pool responses from all blocks for model estimation, including block as a control variable.

Try the live tutorial

The live tutorial is a working SurveyEngine survey. Click through it as a respondent to see the finished result.

Then download the tutorial ZIP file and upload it to your SurveyEngine account to examine how it was built. Open any page in the editor to see the configuration.

Preview the live tutorial or download the ZIP file to load it into your account.