Reification (statistics)
Encyclopedia
In statistics
, reification is the use of an idealized model of a statistical process. The model is then used to make inference
s connecting model results, which imperfectly represent the actual process, with experimental observations.
Also, a process whereby model-derived quantities such as principal components, factors
and latent variable
s are identified, named and treated as if they were directly measurable quantities.
Statistics
Statistics is the study of the collection, organization, analysis, and interpretation of data. It deals with all aspects of this, including the planning of data collection in terms of the design of surveys and experiments....
, reification is the use of an idealized model of a statistical process. The model is then used to make inference
Statistical inference
In statistics, statistical inference is the process of drawing conclusions from data that are subject to random variation, for example, observational errors or sampling variation...
s connecting model results, which imperfectly represent the actual process, with experimental observations.
Also, a process whereby model-derived quantities such as principal components, factors
Factor analysis
Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved, uncorrelated variables called factors. In other words, it is possible, for example, that variations in three or four observed variables...
and latent variable
Latent variable
In statistics, latent variables , are variables that are not directly observed but are rather inferred from other variables that are observed . Mathematical models that aim to explain observed variables in terms of latent variables are called latent variable models...
s are identified, named and treated as if they were directly measurable quantities.