Description: Quasi-experimental analysis is a method used to evaluate the effect of an intervention without random assignment. Unlike randomized experiments, where participants are randomly assigned to control or treatment groups, quasi-experimental analysis relies on pre-existing groups or situations where randomization is not possible for ethical or practical reasons. This approach allows researchers to observe the effects of an intervention in a more natural setting, although it may be subject to selection bias. Key characteristics of quasi-experimental analysis include the use of comparison groups, measuring outcomes before and after the intervention, and applying statistical techniques to control for confounding variables. This method is particularly relevant in fields such as education, public health, and social sciences, where interventions are often implemented in real-world contexts and strict controlled experiments cannot be conducted. Through quasi-experimental analysis, researchers can gain valuable insights into the effectiveness of programs and policies, thereby contributing to informed decision-making and improving practices across various domains.
