Manifest Variable
- Observable quantities that researchers can directly measure (e.g., height, weight, gender).
- Provide concrete data used to test hypotheses and draw conclusions.
- Often used alongside latent variables to infer underlying factors or to control for their influence.
Definition
Section titled “Definition”Manifest variables are those that can be directly observed and measured in a study.
Explanation
Section titled “Explanation”Manifest variables supply concrete, observable data that researchers can measure consistently and analyze. Examples include height, weight, and gender. Manifest variables are frequently used together with latent variables: latent variables are underlying factors that cannot be directly observed but can be inferred from manifest variables. By selecting and measuring appropriate manifest variables, researchers can test hypotheses, draw conclusions, and control for the potential influence of inferred latent factors.
Examples
Section titled “Examples”Height
Section titled “Height”In a study on the relationship between height and income, researchers could directly measure the height of each participant using a tape measure. This allows accurate and consistent collection of height data, which can then be analyzed for correlation with income.
Gender
Section titled “Gender”In a study on the effects of a new medication on anxiety levels, researchers could directly observe and record the gender of each participant. This enables determination of whether the medication’s effectiveness differs between men and women.
Education level and Occupation (to infer socioeconomic status)
Section titled “Education level and Occupation (to infer socioeconomic status)”In the height and income study, researchers could use manifest variables such as education level and occupation to infer the latent variable of socioeconomic status. This permits control for the potential influence of socioeconomic status on the relationship between height and income.
Use cases
Section titled “Use cases”- Providing concrete, observable data to test hypotheses and draw conclusions.
- Serving as inputs for inferring latent variables (e.g., using education and occupation to infer socioeconomic status).
- Allowing researchers to control for the potential influence of underlying factors when analyzing relationships between variables.
Notes or pitfalls
Section titled “Notes or pitfalls”- Careful selection and consistent measurement of manifest variables is important to obtain reliable data and meaningful analysis.
Related terms
Section titled “Related terms”- Latent variable