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Psychometrics

Psychometrics is the science that produces empirical evidence for survey instruments

Psychometrics is the science related to the creation, use, and interpretability of survey instruments.*  There are two primary types of psychometric analysis:  Reliability and validity.

Reliability, as grounded in Classical Test Theory (CTT), relates the the consistency, confidence, and precision of outcomes and survey instruments.

Validity is evidence of internal structure, consequences of testing, interpretability, generalizability, associations, and accuracy of outcomes and survey instruments.

In psychometrics, reliability evidence is usually generated first with a pilot study that postulates a given factor structure for the construct of interest. Validity evidence is then yielded in another larger study that confirms the theory and structure of the construct yielded in the pilot study and construct specification.

​Psychometrics play a pivotal role in creating and validating assessment tools used in clinical practice.

Reliability and validity

Reliability is the stability, consistency and precision of measures and outcomes.
Reliability
Validity is the utility, interpretability, and accuracy of measures and outcomes.
Validity

Principal Components Analysis and Confirmatory Factor Analysis

Principal Components Analysis (PCA) is often performed in tandem with reliability. It reduces survey data and accounts for maximum variance in a construct.
Principal Components Analysis
Confirmatory Factor Analysis (CFA) provides evidence that validates the findings from PCA and reliability analyses. CFA is performed in tandem with validity.
Confirmatory Factor Analysis

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*Furr RM, & Bacharach, VR. (2008). Psychometrics:  An introduction. Thousand Oaks, CA: Sage.

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