1Cademy - Diagnose the methodological issue with the student assistants suggestion of repeating the same sequence ($$A, B, C$$) for every block. Contrast it with the researchers approach of varying the blocks, and explain why varying the blocks is necessary to prevent bias while still achieving the primary goal of block randomization.

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Block Randomization Sequence Example

Case Study

Diagnose the methodological issue with the student assistant's suggestion of repeating the same sequence ( $A, B, C$ ) for every block. Contrast it with the researcher's approach of varying the blocks, and explain why varying the blocks is necessary to prevent bias while still achieving the primary goal of block randomization.

Case context: A researcher plans to assign nine participants to three experimental conditions ( $A$ , $B$ , and $C$ ) using a block randomization technique. She pre-generates a sequence consisting of three blocks: Block 1 ( $A, C, B$ ), Block 2 ( $B, C, A$ ), and Block 3 ( $C, B, A$ ). A student assistant mistakenly believes that the order of conditions within each block does not matter as long as all three conditions are represented in each block, and suggests using a fixed block sequence of ( $A, B, C$ ) repeated three times.

Question: Diagnose the methodological issue with the student assistant's suggestion of repeating the same sequence ( $A, B, C$ ) for every block. Contrast it with the researcher's approach of varying the blocks, and explain why varying the blocks is necessary to prevent bias while still achieving the primary goal of block randomization.

Sample answer: Repeating the same sequence ( $A, B, C$ ) makes the condition assignments highly predictable. For example, the experimenter would know that the 3rd, 6th, and 9th participants will always be assigned to condition $C$ . This predictability can introduce selection bias if the researcher unconsciously alters how they recruit or interact with participants based on their upcoming condition. In contrast, the researcher's approach of varying the sequence in each block (e.g., $A, C, B$ , then $B, C, A$ , then $C, B, A$ ) keeps the assignments unpredictable. Both approaches achieve the primary goal of block randomization—guaranteeing perfectly equal sample sizes after every three participants—but only the varied sequence successfully prevents predictability and potential bias.

Key points:

Repeating the same block sequence makes upcoming condition assignments predictable.
Predictability in condition assignment can lead to selection bias or researcher expectancy effects.
Varying the sequence within each block keeps assignments unpredictable to prevent bias.
Both the repeated and varied approaches guarantee perfectly equal sample sizes after every three participants.

Rubric: The learner must diagnose that repeating a single sequence makes assignments predictable. They must explain that varied block sequences prevent selection/predictability bias while still maintaining the core benefit of equal sample sizes after every three participants.

Updated 2026-05-26

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