Incidental Parameter Problem
- Occurs when extraneous variables (incidental parameters) affect the dependent variable and distort estimation of the independent variable’s effect.
- Can produce biased or misleading estimates if those variables are not controlled.
- Addressed by controlling for extraneous variables (e.g., regression) and ensuring a representative sample.
Definition
Section titled “Definition”The incidental parameter problem, also known as the “nuisance parameter” problem, arises when researchers are trying to estimate the effects of an independent variable on a dependent variable, but other variables (incidental parameters) are also present and may influence the results.
Explanation
Section titled “Explanation”When incidental parameters influence the dependent variable and are not accounted for in the analysis, the estimated effect of the independent variable can be biased or misleading. Controlling for those extraneous variables—through statistical methods such as regression analysis—and carefully selecting a representative sample help isolate the independent variable’s effect and reduce bias.
Examples
Section titled “Examples”Medication and blood pressure
Section titled “Medication and blood pressure”Researchers randomly assign some participants to receive a medication and others a placebo. Participants’ age and gender may also influence blood pressure, and if these factors are not controlled for, the results may be biased. For example, if the study only includes younger men, the effects of the medication on blood pressure may be overestimated.
Education program and student achievement
Section titled “Education program and student achievement”Researchers randomly assign some schools to receive a new education program and others not to. Schools’ socioeconomic status may also influence student achievement, and if this factor is not controlled for, the results may be biased. For example, if the study only includes schools from high-income areas, the effects of the program on student achievement may be underestimated.
Notes or pitfalls
Section titled “Notes or pitfalls”- Failure to control incidental parameters can lead to biased or misleading estimates of the independent variable’s effect.
- Researchers should control extraneous variables (e.g., via regression) and carefully select participants or units of analysis to ensure the sample is representative of the population of interest.
Related terms
Section titled “Related terms”- Nuisance parameter