Abstract
The invariance of oblique factors under random data conditions is investigated as a function of sample size (50, 100, 200), number of variables (15, 30, 45), and number of extracted factors (5, 10).
Keywords
Oblique caseMathematicsStatisticsMeasurement invarianceSample (material)Space (punctuation)Sample size determinationFunction (biology)Computer sciencePhysicsConfirmatory factor analysisStructural equation modeling
Related Publications
Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance
Abstract Measurement invariance is usually tested using Multigroup Confirmatory Factor Analysis, which examines the change in the goodness-of-fit index (GFI) when cross-group co...
Teacher's Corner: Testing Measurement Invariance of Second-Order Factor Models
We illustrate testing measurement invariance in a second-order factor model using a quality of life dataset (n = 924). Measurement invariance was tested across 2 groups at a set...
A Monte-Carlo Study of Confirmatory Factor Analytic Tests of Measurement Equivalence/Invariance
In recent years, confirmatory factor analytic (CFA) techniques have become the most common method of testing for measurement equivalence/invariance (ME/I). However, no study has...
Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance
Two Monte Carlo studies were conducted to examine the sensitivity of goodness of fit indexes to lack of measurement invariance at 3 commonly tested levels: factor loadings, inte...
Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis
Exploratory factor analysis (EFA) is a complex, multi-step process. The goal of this paper is to collect, in one article, information that will allow researchers and practitione...
Publication Info
- Year
- 1971
- Type
- article
- Volume
- 6
- Issue
- 2
- Pages
- 233-241
- Citations
- 27
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
27
OpenAlex
Cite This
JOHN B. NESSELROADE,
Paul B. Baltes,
ERICH W. LABOUVJE
(1971).
EVALUATING FACTOR INVARIANCE IN OBLIQUE SPACE: BASELINE DATA GENERATED FROM RANDOM NUMBERS.
Multivariate Behavioral Research
, 6
(2)
, 233-241.
https://doi.org/10.1207/s15327906mbr0602_4
Identifiers
- DOI
- 10.1207/s15327906mbr0602_4