Investigating the Sensitivity of Goodness-of-Fit Indices to Detect Measurement Invariance in a Bifactor Model

Khojasteh, Jam; Lo, Wen‐Juo

doi:10.1080/10705511.2014.937791

Cited by 37 publications

(35 citation statements)

References 43 publications

(163 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To evaluate the fit of the structural equation models specified to examine the TPACK-attitudes relations, we referred to common guidelines for an Hu & Bentler, 1999;Marsh, Hau, & Grayson, 2005). Nevertheless, these guidelines do not represent "golden rules" (Marsh, Hau, & Wen, 2004) -in fact, they do not fully apply to complex factor structures, such as second-order or nested-factor models (e.g., Khojasteh & Lo, 2015). All models were estimated in the software Mplus 7.3 (Muthén & Muthén, 1998-2015.…”

Section: Discussionmentioning

confidence: 99%

The importance of attitudes toward technology for pre-service teachers' technological, pedagogical, and content knowledge: Comparing structural equation modeling approaches

Scherer

Tondeur

Siddiq

et al. 2018

Computers in Human Behavior

182

View full text Add to dashboard Cite

A large body of literature suggests that attitudes toward technology and its educational use are important determinants of technology acceptance and integration in classrooms. At the same time, teachers' Technological, Pedagogical, and Content Knowledge (TPACK) facilitates the meaningful use of technology for educational purposes. Overall, attitudes toward technology and TPACK play a critical role for technology integration and have been in the focus of many empirical studies. Albeit the attention that has been paid to these two concepts, their relation has not been fully understood. The present study contributes to the advancement of this understanding by examining the relations between three core technology attitudes (i.e., general attitudes towards ICT, attitudes towards ICT in education, and ease of use) and TPACK self-efficacy beliefs, based on a sample of N = 688 Flemish pre-service teachers in 18 teacher-training institutions. Using a variety of structural equation modeling approaches, we describe the TPACK-attitudes relations from multiple perspectives and present a substantivemethodological synergism. The analyses revealed that the attitudes toward technology and TPACK self-beliefs were positively related; yet, differences across the attitudes and TPACK dimensions existed, pointing to the delineation of general and educational perspectives on the use of ICT.

show abstract

Section: Discussionmentioning

confidence: 99%

The importance of attitudes toward technology for pre-service teachers' technological, pedagogical, and content knowledge: Comparing structural equation modeling approaches

Scherer

Tondeur

Siddiq

et al. 2018

Computers in Human Behavior

182

View full text Add to dashboard Cite

show abstract

“…Moreover, we adopted goodness of fit criteria for nested models noted by Chen (2007) [47], with ∆CFI ≥ −0.10, ∆Gamma ≥ −0.08, ∆RMSEA ≥ 0.015, ∆Mc ≥ −0.03 signal model rejection (Cf. Khojasteh and Lo (2012 ; Table 17; [48]) for alternative recommendations by different authors).…”

Section: Assessment Of Measurement Invariancementioning

confidence: 99%

Filling in the Gaps: The Association between Intelligence and Both Color and Parent-Reported Ancestry in the National Longitudinal Survey of Youth 1997

Lasker²,

Kirkegaard³

et al. 2019

Psych

View full text Add to dashboard Cite

Little research has dealt with intragroup ancestry-related differences in intelligence in Black and White Americans. To help fill this gap, we examined the association between intelligence and both color and parent-reported ancestry using the NLSY97. We used a nationally-representative sample, a multidimensional measure of cognitive ability, and a sibling design. We found that African ancestry was negatively correlated with general mental ability scores among Whites (r = −0.038, N = 3603; corrected for attenuation, rc = −0.245). In contrast, the correlation between ability and parent-reported European ancestry was positive among Blacks (r = 0.137, N = 1788; rc = 0.344). Among Blacks, the correlation with darker skin color, an index of African ancestry, was negative (r = −0.112, N = 1455). These results remained with conspicuous controls. Among Blacks, both color and parent-reported European ancestry had independent effects on general cognitive ability (color: β = −0.104; ancestry: β = 0.118; N = 1445). These associations were more pronounced on g-loaded subtests, indicating a Jensen Effect for both color and ancestry (rs = 0.679 to 0.850). When we decomposed the color results for the African ancestry sample between and within families, we found an association between families, between singletons (β = −0.153; N = 814), and between full sibling pairs (β = −0.176; N = 225). However, we found no association between full siblings (β = 0.027; N = 225). Differential regression to the mean results indicated that the factors causing the mean group difference acted across the cognitive spectrum, with high-scoring African Americans no less affected than low-scoring ones. We tested for measurement invariance and found that strict factorial invariance was tenable. We then found that the weak version of Spearman’s hypothesis was tenable while the strong and contra versions were not. The results imply that the observed cognitive differences are primarily due to differences in g and that the Black-White mean difference is attributable to the same factors that cause differences within both groups. Further examination revealed comparable intraclass correlations and absolute differences for Black and White full siblings. This implied that the non-shared environmental variance components were similar in magnitude for both Blacks and Whites.

show abstract

“…Cheung and Rensvold (2002) proposed similar cut-off values for the CFI (ΔCFI ≤ -.010), whereas Meade, Johnson, and Braddy (2008) provided stricter values, ΔCFI ≤ -.002. Finally, Khojasteh and Lo (2015) indicated more conservative criteria for the RMSEA in situations, where the measurement model follows a bi-factor structure, ΔCFI ≤ -0.04, ΔRMSEA ≤ .034, ΔSRMR ≤ .030. In addition, χ 2 difference testing can be employed (Brown, 2015).…”

Section: Measurement Invariance Testingmentioning

confidence: 99%

“…Furthermore, their performance varies with respect to sample size, the number of latent variables, the treatment of the data (continuous vs. categorical), the number of groups, the type of measurement invariance tested, and the factor structure specified (Khojasteh & Lo, 2015;Meade et al, 2008;Rutkowski & Svetina, 2014). In the present study, we followed the cut-off-values Khojasteh and Lo (2015) suggested, because they enable us to evaluate the invariance of complex measurement models (e.g., nested factor models).…”

Section: Measurement Invariance Testingmentioning

confidence: 99%

On the quest for validity: Testing the factor structure and measurement invariance of the technology-dimensions in the Technological, Pedagogical, and Content Knowledge (TPACK) model

Scherer

Tondeur

Siddiq

2017

Computers & Education

136

View full text Add to dashboard Cite

show abstract

Investigating the Sensitivity of Goodness-of-Fit Indices to Detect Measurement Invariance in a Bifactor Model

Cited by 37 publications

References 43 publications

The importance of attitudes toward technology for pre-service teachers' technological, pedagogical, and content knowledge: Comparing structural equation modeling approaches

The importance of attitudes toward technology for pre-service teachers' technological, pedagogical, and content knowledge: Comparing structural equation modeling approaches

Filling in the Gaps: The Association between Intelligence and Both Color and Parent-Reported Ancestry in the National Longitudinal Survey of Youth 1997

On the quest for validity: Testing the factor structure and measurement invariance of the technology-dimensions in the Technological, Pedagogical, and Content Knowledge (TPACK) model

Contact Info

Product

Resources

About