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Randomization Does Not Help Much, Comparability Does.
1Nordhausen University of Applied Sciences, Nordhausen, Germany.
Plos One
|July 21, 2015
Summary
Randomization in experiments often leads to group imbalance, challenging its validity in small to medium samples. Comparability and sound theory are more reliable for robust experimental conclusions.
Area of Science:
- Statistics
- Experimental Design
Background:
- Randomization is widely accepted for controlling nuisance factors in experiments.
- R.A. Fisher advocated randomization to mitigate confounding variables.
Purpose of the Study:
- To challenge the prevailing view on the effectiveness of randomization.
- To investigate the quantitative and qualitative arguments supporting randomization.
Main Methods:
- Analysis of simple mathematical models to assess group balance.
- Non-technical discussion of traditional arguments for randomization, including Frequentist/Bayesian perspectives.
Main Results:
- Mathematical models show significant group imbalance due to randomization in small to medium samples.
- Confounding is common, not exceptional, with random allocation.
- The benefits of randomization are questioned, while comparability is highlighted.
Conclusions:
- The optimism surrounding randomization in experimental design is questionable.
- Comparability and well-established background theory are crucial for valid experimental conclusions.
- Systematic construction of exchangeable groups is advisable for classical experimentation.
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