Betweensubject

Between-subjects design, also known as independent-groups design, is an experimental design in which different participants are assigned to each level of the independent variable. In this setup, each participant experiences only one condition, in contrast to within-subjects designs where the same participants encounter multiple conditions. This arrangement minimizes carryover or practice effects and is useful when the treatment cannot be easily washed out or might interact with itself over time.

Allocation and control are central concerns. Random assignment is commonly used to create equivalent groups and reduce selection bias. Researchers may also employ matching, blocking, or stratified randomization to balance key characteristics (such as age or baseline ability) across conditions. While randomization helps control for known and unknown confounds, the groups can still differ on average, especially with small samples.

Statistical analysis for between-subjects designs typically relies on tests that compare group means, such as t-tests for two groups or analysis of variance (ANOVA) for more than two groups or factors. Assumptions include independence of observations, normal distribution within groups, and homogeneity of variances. When these assumptions are violated, nonparametric tests or robust methods may be used.

Advantages of between-subjects designs include simplicity, reduced risk of carryover effects, and suitability for certain interventions. Limitations include the need for larger sample sizes to achieve adequate statistical power and greater susceptibility to individual differences across groups. Quasi-experimental variants may employ nonrandom assignment, which can introduce additional biases.

Applications commonly arise in psychology, education, and medicine, where comparisons between different treatments, conditions, or groups are of interest.