Subgroup analysis
Subgroup Analysis
Subgroup Analysis (pronunciation: /ˈsʌbˌgruːp əˈnælɪsɪs/) is a type of statistical analysis used in clinical trials and epidemiological research. It involves separating out data from a larger population to identify patterns or trends within specific subgroups.
Etymology
The term "subgroup analysis" is derived from the words "subgroup", meaning a division or subset of a larger group, and "analysis", which refers to the detailed examination of the elements or structure of something.
Definition
Subgroup analysis is a method used in research to examine the relationship between the treatment effect and a specific characteristic (such as age, gender, or disease severity) within a study population. This is done by dividing the population into subgroups based on these characteristics and then analyzing the data separately for each subgroup.
Related Terms
- Interaction effect: This refers to the situation where the effect of one variable on the outcome variable differs depending on the level of another variable. In the context of subgroup analysis, it refers to the different effects of a treatment in different subgroups.
- Stratified analysis: This is a type of subgroup analysis where the data is divided into strata, or layers, based on certain characteristics. The data is then analyzed separately for each stratum.
- Covariate: This is a variable that may affect the outcome of a study but is not the variable of interest. In subgroup analysis, covariates are often used to adjust the results to account for potential confounding factors.
- Confounding factor: This is a variable that is related to both the treatment and the outcome, and can therefore distort the apparent relationship between them. In subgroup analysis, confounding factors are often controlled for to ensure that any observed effects are due to the treatment rather than these factors.
External links
- Medical encyclopedia article on Subgroup analysis
- Wikipedia's article - Subgroup analysis
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