This study examines the psychometric features of a General Aptitude Test–Verbal Part, which is used with assessments of high school graduates in Saudi Arabia. The data supported a bifactor model, with one general factor and three content domains (Analogy, Sentence Completion, and Reading Comprehension) as latent aspects of verbal aptitude.
BartolucciF.MontanariG. E.PandolfiS. (2012). Dimensionality of the latent structure and item selection via latent class multidimensional IRT models. Psychometrika, 77, 782–802.
2.
BejarI. I. (1980). A procedure for investigating the unidimensionality of achievement tests based on item parameter estimates. Journal of Educational Measurement, 17, 283–296.
3.
BollenK. A. (1989). Structural equations with latent variables. New York, NY: Wiley.
4.
CarrolJ. B. (1941). A factor analysis of verbal abilities. Psychometrika, 6, 279–307.
5.
CarrollJ. B. (1983). The difficulty of a test and its factor composition revisited. In MessickS.WainerH. (Eds.), Principals of modern psychological measurement: A festschrift for Frederic M. Lord. Hillsdale, NJ: Erlbaum.
6.
ChenF. F.WestS. G.SousaK. H. (2006). A comparison of bifactor and second-order models of quality of life. Multivariate Behavioral Research, 41, 189–225.
7.
CoffmanW. E. (1966). A factor analysis of the verbal section of the scholastic aptitude test (RB-66-30). Princeton, NJ: Educational Testing Service.
8.
CookL. L.DoransN. J.EignorD. R. (1988). An assessment of the dimensionality of three SAT-Verbal editions. Journal of Educational Statistics, 13, 19–43.
9.
DavisonM. L. (1985). Multidimensional scaling versus component analysis of test inter-correlations. Psychological Bulletin, 97, 94–105.
10.
DebelakR.TranU. S. (2013). Principal component analysis of smoothed tetrachoric correlation matrices as a measure of dimensionality. Educational and Psychological Measurement, 73, 63–77.
11.
DimitrovD. M. (2012). Statistical methods for validation of assessment scale data in counseling and related fields. Alexandria, VA: American Counseling Association.
12.
DoransN. J.LawrenceI. M. (1999). The role of the unit of the analysis in dimensionality assessment (RR-99-14). Princeton, NJ: Educational Testing Service.
13.
FinchH.HabingB. (2007). Performance of DIMTEST and NOHARM based statistics for testing unidimensionality. Applied Psychological Measurement, 31, 292–307.
GreenS. B. (1983). Identifiability of spurious factors using linear factor analysis with binary variables. Applied Psychological Measurement, 7, 139–147.
16.
HuL. T.BentlerP. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.
17.
JöreskogK. G. (1971). Statistical analysis of sets of congeneric tests. Psychometrika, 36, 109–133.
18.
KishtonJ. M.WidamanK. F. (1994). Unidimensional versus domain representative parceling of questionnaire items: An empirical example. Educational and Psychological Measurement, 54, 757–765.
19.
LawrenceI. M.DoransN. J. (1987). An assessment of the dimensionality of SAT-Mathematical. Paper presented at the Annual Meeting of the National Council on Measurement in Education, Washington, DC.
20.
MarshH. W.HauK. T.WenZ. (2004). In search of golden rules: Comment on hypothesis testing approaches to setting cutoff values for fit indexes and dangers in over-generalizing findings. Structural Equation Modeling, 11, 320–341.
21.
MearaK.RobinF.SireciS. G. (2000). Using multidimensional scaling to assess the dimensionality of dichotomous item data. Multivariate Behavioral Research, 35, 229–259.
22.
MislevyR. J. (1986). Recent developments in the factor analysis of categorical variables. Journal of Educational Statistics, 11, 3–31.
23.
MuthénL. K.MuthénB. O. (2012). Mplus user’s guide. Los Angeles, CA: Muthén & Muthén.
24.
NandakumarR.YuF. (1996). Empirical validation of DIMTEST on nonnormality ability distributions. Journal of Educational Measurement, 33, 355–368.
25.
RaykovT. (2007). Evaluation of weighted scale reliability and criterion validity: A latent variable modeling approach. Measurement and Evaluation in Counseling and Development, 40(1), 42–52.
26.
RaykovT.DimitrovD. M.AsparouhovT. (2010). Evaluation of scale reliability with binary measures using latent variable modeling. Structural Equation Modeling, 17, 265–279.
27.
RaykovT.PohlS. (2012). On studying common variance in multiple component measuring instrument. Educational and Psychological Measurement, 73, 191–209.
28.
RaykovT.PohlS. (2013). Essential unidimensionality examination for multi-component scales: An interrelationship decomposition approach. Educational and Psychological Measurement, 73, 581–600.
29.
ReiseS. P.MooreT. M.HavilandM. G. (2010). Bifactor models and rotations: Exploring the extent to which multidimensional data yield univocal scale scores. Journal of Personality Assessment, 92, 544–559.
30.
ReiseS. P.MorizotJ.HaysR. D. (2007). The role of the bifactor model in resolving dimensionality issues in health outcomes measures. Journal of Quality of Life Research, 16, 19–31.
31.
SmithR. M. (1996). A comparison of methods for determining dimensionality in Rasch measurement. Structural Equation Modeling, 3(1), 25–40.
32.
SmithR. M.MiaoC. Y. (1994). Assessing unidimensionality for Rasch measurement. In WilsonM. (Ed.), Objective measurement: Theory into practice (Vol. 2). Greenwich, CT: Ablex.
33.
SochaA.DeMarsC. E. (2013). A note on specifying the guessing parameter in ATFIND and DIMTEST. Applied Psychological Measurement, 37, 87–92.
34.
StoutW. E. (1987). A nonparametric approach for assessing latent trait dimensionality. Psychometrika, 55, 293–325.
35.
TakaneY.de LeeuwJ. (1987). On the relationship between item response theory and factor analysis of discretized variables. Psychometrika, 52, 393–408.
36.
WalkerC. M.AzenR.SchmittT. (2006). Statistical versus substantive dimensionality: The effect of distributional differences on dimensionality assessment using DIMTEST. Educational and Psychological Measurement, 66, 721–738.
37.
YuC.-Y.MuthénB. (2002). Evaluation of model fit indices for latent variable models with categorical and continuous outcomes. Paper presented at the annual meeting of the American Educational Research Association, New Orleans, LA.
38.
YuanK.BentlerP. M.KanoY. (1997). On averaging variables in a confirmatory factor analysis. Behaviormetrika, 24, 71–83.
39.
ZhangJ.StoutW. (1999). The theoretical detect index of dimensionality and its application to approximate simple structure. Psychometrika, 64, 231–249.