How to use randomization techniques in experiments?

Randomization techniques in experiments involve assigning study units (like participants or plots) to different treatment groups using a chance mechanism, ensuring each unit has a known probability of allocation. This is a fundamental and feasible method to establish causality by minimizing bias. Key principles include employing a truly random process for sequence generation, implementing allocation concealment to prevent selection bias before assignment, and maintaining the integrity of the randomization after assignment. It crucially depends on an adequate sample size for the probability mechanism to effectively balance known and unknown confounders across groups. While applicable across various experimental designs (e.g., RCTs, field trials, lab studies), its effectiveness requires proper execution and adherence to protocols; common failure points include predictable sequences or breaches of concealment. To implement randomization, first define the target population, experimental units, and interventions. Then, select an appropriate technique (e.g., simple, block, or stratified randomization) based on design needs. Generate the allocation sequence using a verifiable random method (random number generator, tables). Crucially, conceal this sequence until irrevocable assignment occurs. Finally, rigorously assign units to groups strictly according to the pre-generated sequence, documenting the process. This ensures comparability, enhances internal validity, and supports unbiased causal inference.