Bayesian item response theory models for measurement variance

Verhagen, Josine

doi:10.3990/1.9789036534697

Cited by 3 publications

(4 citation statements)

References 91 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Model type 3 lets both intercepts and factor loadings vary across betweenlevel units. This has been discussed in De Jong et al (2007), De Boeck (2008), de Jong and Steenkamp (2010), Frederickx et al (2010), Fox (2010, Fox and Verhagen (2011), Verhagen and Fox (2013), Verhagen (2013), and Asparouhov and Muthén (2015). Bayesian estimation is needed because random loadings with maximum likelihood estimation give rise to numerical integration with many dimensions which is computationally intractable.…”

Section: Model Type 3: Random Intercepts Random Loadingsmentioning

confidence: 96%

Recent Methods for the Study of Measurement Invariance With Many Groups

Muthén

2017

Sociological Methods & Research

233

297

View full text Add to dashboard Cite

This article reviews and compares recently proposed factor analytic and item response theory approaches to the study of invariance across groups. Two methods are described and contrasted. The alignment method considers the groups as a fixed mode of variation, while the random-intercept, random-loading two-level method considers the groups as a random mode of variation. Both maximum likelihood and Bayesian analyses are applied. A survey of close to 50,000 subjects in 26 countries is used as an illustration. In addition, the two methods are studied by Monte Carlo simulations. A list of considerations for choosing between the two methods is presented.

show abstract

Section: Model Type 3: Random Intercepts Random Loadingsmentioning

confidence: 96%

Recent Methods for the Study of Measurement Invariance With Many Groups

Muthén

2017

Sociological Methods & Research

233

297

View full text Add to dashboard Cite

show abstract

“…For an updated overview, see: http://www.lisdatacenter.org/our-data/lisdatabase/datasets-information/ 2 The literature on comparability of measurements across countries and / or time is well developed(Davidov, Schmidt, & Biliet, 2011;Verhagen, 2012;Kline, 2005). However, the methodology in this literature is mostly based on a generalised-latent variable approach.…”

mentioning

confidence: 99%

Family policy outcomes: Combining Institutional and Demographic Explanations of Women’s Employment and Earnings Inequality in OECD Countries, 1975-2005

Nieuwenhuis¹

2016

Preprint

View full text Add to dashboard Cite

Women’s employment and earnings, as well as earnings inequality, have been rising in OECD countries in recent decades. This dissertation answers questions pertaining to how family policies have facilitated women in combining motherhood and employment, and how women’s earnings have affected inequality among households. Based on well over a million person-level observations, this study covers 18 OECD countries and a period from 1975 to 2005.Work-family reconciliation policies were shown to reduce the employment gap between mothers and women without children, while policies financially supporting families with children enlarge this motherhood-employment gap. Very long periods of leave, however, negatively affect the employment of mothers. More educated mothers benefit more from reconciliation policies than the less educated. Women’s rising earnings were found to have attenuated inequality among households. Family policy arrangements that facilitate women’s employment not only contribute to smaller inequality within households, but also among households.

show abstract

“…For the group-specific parameters, the prior structure can be defined in several different ways. One way is to assume a multilevel structure for the group-specific item parameters (De Jong et al, 2007;Fox, 2010;Fox and Verhagen, 2010;Verhagen andFox, 2013a, 2013b). Let μ b 0 denote the average difficulty of all items and let u k denote the average deviation of item k from the population mean difficulty.…”

Section: Models For Random Item Parametersmentioning

confidence: 99%

“…. , 11, and group j = 1 or 2, are treated as fixed (e.g., De Boeck, 2008;Frederickx et al, 2010;Verhagen, 2012). An item k is measurement invariant when a male or female with the same latent trait θ has the same probability of a certain response (Mellenbergh, 1989;Millsap and Everson, 1993), that is, b k1 = b k2 .…”

Section: Bayesian Model Comparisonmentioning

confidence: 99%

Complex Latent Variable Modeling in Educational Assessment

Fox

Marsman

Mulder

et al. 2014

Communications in Statistics - Simulation and Computation

Self Cite

View full text Add to dashboard Cite

Bayesian item response theory models have been widely used in different research fields. They support measuring constructs and modeling relationships between constructs, while accounting for complex test situations (e.g., complex sampling designs, missing data, heterogenous population). Advantages of this flexible modeling framework together with powerful simulation-based estimation techniques are discussed. Furthermore, it is shown how the Bayes factor can be used to test relevant hypotheses in assessment using the College Basic Academic Subjects Examination (CBASE) data.

show abstract

Bayesian item response theory models for measurement variance

Cited by 3 publications

References 91 publications

Recent Methods for the Study of Measurement Invariance With Many Groups

Recent Methods for the Study of Measurement Invariance With Many Groups

Family policy outcomes: Combining Institutional and Demographic Explanations of Women’s Employment and Earnings Inequality in OECD Countries, 1975-2005

Complex Latent Variable Modeling in Educational Assessment

Contact Info

Product

Resources

About