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Create Experimental Conditions

Create condition sets for random assignment, stratified assignment, or routing based on an earlier variable.

When To Use Experimental Conditions

Experimental conditions let you assign respondents to treatment arms, control arms, information treatments, survey branches, or study paths. In Domandata, condition sets support randomized and rule-based assignment for academic survey experiments and social science research designs.

Flow: Conditions and Routing

Use conditions when different respondents should see different blocks, when an experiment needs random assignment, or when assignment depends on a previous answer or variable. For a study-level guide, see Online Survey Experiments.

Create A Condition Set

  1. Step 1: Build the blocks first. In Block Builder, create the blocks for the control arm, treatment arms, outcomes, and end screens.

    Step 1: Add blocks in Block Builder

  2. Step 2: Open Flow. Select the Flow tab in the survey editor after the block list is mostly stable.

    Step 2: Open Flow canvas

  3. Step 3: Add a condition set. Name it after the design decision it controls, such as Main Experiment, Message Treatment, or Eligibility Path.

    Step 3: Add and name a condition set

  4. Step 4: Set the number of arms. Add the conditions you need and name each arm clearly, such as Control, Treatment A, and Treatment B.

    Step 4: Set condition arms

  5. Step 5: Choose assignment rules. Set random percentages, stratification, or by-variable assignment before connecting the paths; check Sample Allocation Across Condition Arms if cell size matters.

    Step 5: Choose assignment rules

  6. Step 6: Connect each arm. Route every condition to the block respondents should see next, including fallback paths; use Branching and Skip Logic for more complex routes.

    Step 6: Connect condition arms to blocks

Choose An Assignment Mode

  • Random Assignment assigns respondents to arms using weighted-random probabilities. Use equal splits for simple experiments or custom percentages for planned unequal allocation.
  • Stratify by variable keeps random assignment balanced within groups defined by a variable, such as country, party, gender, school, or quota status.
  • By Variable assigns respondents deterministically based on a survey answer or variable that appears earlier in the flow.

Block Builder: Multiple Choice (By Variable Source)

Use Conditions With Question Types

Many research survey question types can feed assignment logic. Use Multiple Choice or Dropdown questions for discrete assignment, Slider or Short Answer questions for numeric ranges, and Grid Matrix questions for repeated measures. Use Conjoint questions when the experimental task itself is a randomized preference design.

Block Builder: Question Type

Preview And Protect The Design

Preview every major path before publishing. Confirm that each arm reaches the correct block, that random assignment percentages total 100 percent, that by-variable sources appear before the split, and that fallback arms behave as expected.

If each arm needs a target number of completed responses, add quotas in Deploy. See Set Survey Quotas. For planning expected n by arm, see Sample Allocation Across Condition Arms.

Preview: Walk Each Arm

Related Help

  • Set Survey Quotas
  • Publish and Share a Research Survey
  • Create Your First Academic Research Survey