IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i5p770-d1351541.html
   My bibliography  Save this article

Examining Differences of Invariance Alignment in the Mplus Software and the R Package Sirt

Author

Listed:
  • Alexander Robitzsch

    (IPN–Leibniz Institute for Science and Mathematics Education, Olshausenstraße 62, 24118 Kiel, Germany
    Centre for International Student Assessment (ZIB), Olshausenstraße 62, 24118 Kiel, Germany)

Abstract

Invariance alignment (IA) is a multivariate statistical technique to compare the means and standard deviations of a factor variable in a one-dimensional factor model across multiple groups. To date, the IA method is most frequently estimated using the commercial Mplus software. IA has also been implemented in the R package sirt. In this article, the performance of IA in the software packages Mplus and R are compared. It is argued and empirically shown in a simulation study and an empirical example that differences between software packages are primarily the cause of different identification constraints in IA. With a change of the identification constraint employing an argument in the IA function in sirt, Mplus and sirt resulted in comparable performance. Moreover, in line with previous work, the simulation study also highlighted that the tuning parameter ε = 0.001 in IA is preferable to ε = 0.01 . Furthermore, an empirical example raises the question of whether IA, in its current implementations, behaves as expected in the case of many groups.

Suggested Citation

  • Alexander Robitzsch, 2024. "Examining Differences of Invariance Alignment in the Mplus Software and the R Package Sirt," Mathematics, MDPI, vol. 12(5), pages 1-16, March.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:5:p:770-:d:1351541
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/5/770/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/5/770/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. William Meredith, 1993. "Measurement invariance, factor analysis and factorial invariance," Psychometrika, Springer;The Psychometric Society, vol. 58(4), pages 525-543, December.
    2. Ioannis Tsaousis & Fathima M. Jaffari, 2023. "Identifying Bias in Social and Health Research: Measurement Invariance and Latent Mean Differences Using the Alignment Approach," Mathematics, MDPI, vol. 11(18), pages 1-15, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Johan Oud & Manuel Voelkle, 2014. "Do missing values exist? Incomplete data handling in cross-national longitudinal studies by means of continuous time modeling," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3271-3288, November.
    2. Liat Ayalon, 2018. "Perceived Age Discrimination: A Precipitator or a Consequence of Depressive Symptoms?," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 73(5), pages 860-869.
    3. Steven Andrew Culpepper & Herman Aguinis & Justin L. Kern & Roger Millsap, 2019. "High-Stakes Testing Case Study: A Latent Variable Approach for Assessing Measurement and Prediction Invariance," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 285-309, March.
    4. Ihsana Sabriani Borualogo & Ferran Casas, 2023. "Bullying Victimisation and Children’s Subjective Well-being: A Comparative Study in Seven Asian Countries," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 16(1), pages 1-27, February.
    5. Wilson, Christopher J. & Bowden, Stephen C. & Byrne, Linda K. & Joshua, Nicole R. & Marx, Wolfgang & Weiss, Lawrence G., 2023. "The cross-cultural generalizability of cognitive ability measures: A systematic literature review," Intelligence, Elsevier, vol. 98(C).
    6. Janina Isabel Steinert & Lucie Dale Cluver & G. J. Melendez-Torres & Sebastian Vollmer, 2018. "One Size Fits All? The Validity of a Composite Poverty Index Across Urban and Rural Households in South Africa," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(1), pages 51-72, February.
    7. Paul MUKUCHA & Divaries Cosmas JARAVAZA & Forbes MAKUDZA, 2022. "Towards Gender-Based Market Segmentation: The Differential Influence of Gender on Dining Experiences in the University Cafeteria Industry," Management and Economics Review, Faculty of Management, Academy of Economic Studies, Bucharest, Romania, vol. 7(2), pages 182-200, June.
    8. Ankica Kosic & Tamara Džamonja Ignjatović & Nebojša Petrović, 2021. "A Cross-Cultural Study of Distress during COVID-19 Pandemic: Some Protective and Risk Factors," IJERPH, MDPI, vol. 18(14), pages 1-15, July.
    9. Amber Mosewich & Valerie Hadd & Peter Crocker & Bruno Zumbo, 2013. "Invariance Testing of the SF-36 Health Survey in Women Breast Cancer Survivors: Do Personal and Cancer-related Variables Influence the Meaning of Quality of Life Items?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 110(2), pages 559-577, January.
    10. Allyson S. Graf & Meagan A. Ramsey & Julie Hicks Patrick & Amy L. Gentzler, 2016. "Dark Storm Clouds and Rays of Sunshine: Profiles of Negative and Positive Rumination About Daily Hassles and Uplifts," Journal of Happiness Studies, Springer, vol. 17(6), pages 2257-2276, December.
    11. Hofmans, J. & Pepermans, R. & Loix, E., 2009. "Measurement invariance matters: A case made for the ORTOFIN," Journal of Economic Psychology, Elsevier, vol. 30(4), pages 667-674, August.
    12. Stéfanie André, 2014. "Does Trust Mean the Same for Migrants and Natives? Testing Measurement Models of Political Trust with Multi-group Confirmatory Factor Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 115(3), pages 963-982, February.
    13. Pei-Chen Wu, 2010. "Differential Functioning of the Chinese Version of Beck Depression Inventory-II in Adolescent Gender Groups: Use of a Multiple-Group Mean and Covariance Structure Model," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 96(3), pages 535-550, May.
    14. Roberta De Vito & Ruggero Bellio & Lorenzo Trippa & Giovanni Parmigiani, 2019. "Multi‐study factor analysis," Biometrics, The International Biometric Society, vol. 75(1), pages 337-346, March.
    15. Francisco J. Conejo & Lawrence F. Cunningham & Clifford E. Young, 2020. "Revisiting the Brand Luxury Index: new empirical evidence and future directions," Journal of Brand Management, Palgrave Macmillan, vol. 27(1), pages 108-122, January.
    16. Eldad Davidov & Stefan Thörner & Peter Schmidt & Stefanie Gosen & Carina Wolf, 2011. "Level and change of group-focused enmity in Germany: unconditional and conditional latent growth curve models with four panel waves," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 481-500, December.
    17. P. Couper, Mick & Cernat, Alexandru & Beth Ofstedal, Mary, 2015. "Estimation of mode effects in the Health and Retirement Study using measurement models," ISER Working Paper Series 2015-19, Institute for Social and Economic Research.
    18. Eunju Jung & Yongjin Lee, 2020. "College Students’ Entrepreneurial Mindset: Educational Experiences Override Gender and Major," Sustainability, MDPI, vol. 12(19), pages 1-28, October.
    19. Ligon, Ethan, 2017. "Estimating household welfare from disaggregate expenditures," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt5gc4h1fm, Department of Agricultural & Resource Economics, UC Berkeley.
    20. Jule Specht & Boris Egloff & Stefan C. Schmukle, 2012. "Examining Mechanisms of Personality Maturation: The Impact of Life Satisfaction on the Development of Big Five Personality Traits," SOEPpapers on Multidisciplinary Panel Data Research 455, DIW Berlin, The German Socio-Economic Panel (SOEP).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:5:p:770-:d:1351541. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.