Ignorability
- Some variables can be omitted from an analysis without changing its validity when they are effectively random or irrelevant.
- Random assignment (for example, in an experiment) is a common situation that produces ignorability.
- Ignorability lets researchers focus on factors that matter to the study outcome.
Definition
Section titled “Definition”Ignorability is a statistical concept referring to the condition in which certain factors or variables can be “ignored” or left out of a statistical analysis without affecting the validity of the results, because those factors or variables are considered to be “random” or “not relevant” to the analysis.
Explanation
Section titled “Explanation”When a factor (such as group or school assignment) is unrelated to the outcome of interest—typically because it is assigned at random—it does not bias the comparison between groups. In that case the factor can be treated as irrelevant to the analysis, and omitting it does not undermine the validity of conclusions. This permits researchers to concentrate on variables that are relevant to the question under study.
Examples
Section titled “Examples”Randomized medication trial
Section titled “Randomized medication trial”Participants are randomly assigned to one of two groups: an experimental group that receives a new medication and a control group that receives a placebo. Because group assignment is random and not related to the medication’s effectiveness, the group assignment is considered “random” or “irrelevant” and can be ignored in the statistical analysis.
Randomized educational program at schools
Section titled “Randomized educational program at schools”Schools are randomly assigned either to an experimental group that receives a new program or to a control group that does not. Since school assignment is not related to the program’s effectiveness, the assignment is considered “random” or “irrelevant” and can be ignored in the statistical analysis.