MATCHED PAIR ANALYSIS Meaning and
Definition
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Matched pair analysis is a statistical technique used in research and data analysis to compare two groups that are closely matched on a specific characteristic or set of variables. It involves selecting pairs of participants or cases that are similar in terms of certain traits, and then comparing the outcomes or results of each pair to draw meaningful conclusions.
The purpose of matched pair analysis is to control for potential confounding variables or biases that may influence the relationship between the independent and dependent variables. By matching individuals or cases on key characteristics such as age, gender, or socioeconomic status, researchers can eliminate or minimize the effects of these variables on the results.
This technique is often employed in medical and social research, where it is not feasible or ethical to randomly assign participants to different groups. For example, in a study examining the effectiveness of a new medication, researchers may match individuals with similar medical histories, age, and severity of the condition. One person in each matched pair would be assigned to the treatment group while the other serves as a control, so that the impact of the medication can be accurately assessed.
Matched pair analysis allows for a more precise evaluation of the intervention, as it ensures that any observed differences in outcomes can be attributed to the treatment being investigated rather than other factors. The results of matched pair analysis can provide valuable insights and support evidence-based decision-making in various academic, scientific, and professional fields.
Common Misspellings for MATCHED PAIR ANALYSIS
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