In statistics, observable variable or observable quantity, as opposed to latent variable, is a variable that can be observed and directly measured.

A variable that can be directly measured or observed. It is the opposite of a latent variable, which can not be directly observed. Manifest variables are used in latent variable statistical models, which test the relationships between a set of manifest variables and a set of latent variables. Manifest variables are considered either continuous or categorical (a countable range).

Statisticians use several different analysis tests when examining manifest variables and latent variables. The four most frequently used models are factor analysis, latent trait analysis, latent profile analysis, and latent class analysis. Which model is ultimately used depends on whether the manifest variables are continuous or categorical, and whether the latent variables are continuous or categorical.

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Statistical models include factor analysis, latent trait analysis, latent profile analysis, and latent class analysis.

Factor Analysis.

Manifest variables are either continuous or categorical.

A latent variable is a variable that can not be directly measured or observed.

Latent Trait Analysis.

Latent Class Analysis.