Sage Journals: Discover world-class research

Abstract

A latent variable modeling approach that can be used to examine whether several psychometric tests are parallel is discussed. The method consists of sequentially testing the properties of parallel measures via a corresponding relaxation of parameter constraints in a saturated model or an appropriately constructed latent variable model. The underlying procedure is readily used in cases with at least three single measures studied for parallelism and is directly extended to the setting of multiple-component measuring instruments. The methodological limitations concerning intended attempts to test if two given measures are parallel are also explicated. The proposed modeling approach is illustrated with an example.

Keywords

latent variable modeling multiple components parallel measures parameter constraint saturated model

Get full access to this article

View all access options for this article.

References

Bentler

P. M.

(2004). EQS structural equation program manual. Encino, CA: Multivariate Software.

Bentler

P. M.

Satorra

(2010). Testing model nesting and equivalence. Psychological Methods, 15, 122-132.

Bollen

K. A.

(1989). Structural equations with latent variables. New York, NY: Wiley.

Crocker

Algina

(1986). Introduction to classical and modern test theory. Fort Worth, TX: Harcourt Brace Jovanovich.

Gulliksen

(1950). Theory of mental tests. New York, NY: Wiley.

Hays

W. L.

(1994). Statistics. Fort Worth, TX: Harcourt Brace Jovanovich.

Johnson

R. A.

Wichern

D. W.

(2002). Applied multivariate statistical analysis. Upper Saddle River, NJ: Prentice Hall.

Jöreskog

K. G.

(1971). Statistical analysis of sets of congeneric tests. Psychometrika, 36, 109-133.

Lord

Novick

(1968). Statistical theories of mental test scores. Reading, MA: Addison-Wesley.

10.

McDonald

R. P.

(1999). Test theory: A unified treatment. Mahwah, NJ: Lawrence Erlbaum.

11.

Muthén

B. O.

(2002). Beyond SEM: General latent variable modeling. Behaviormetrika, 29, 87-117.

12.

Muthén

L. K.

Muthén

B. O.

(2010). Mplus user’s guide. Los Angeles, CA: Muthén & Muthén.

13.

Raykov

Marcoulides

G. A.

(2011). Introduction to psychometric theory. New York, NY: Taylor & Francis.

14.

Zimmerman

D. W.

(1975). Probability measures, Hilbert spaces, and the axioms of classical test theory. Psychometrika, 30, 221-232.

Examining Parallelism of Sets of Psychometric Measures Using Latent Variable Modeling

Abstract

Keywords

Get full access to this article

References