IDEAS home Printed from https://ideas.repec.org/a/spr/alstar/v102y2018i4d10.1007_s10182-018-0320-0.html
   My bibliography  Save this article

Varying levels of anomie in Europe: a multilevel analysis based on multidimensional IRT models

Author

Listed:
  • Lara Fontanella

    (University of Chieti-Pescara)

  • Annalina Sarra

    (University of Chieti-Pescara)

  • Pasquale Valentini

    (University of Chieti-Pescara)

  • Simone Zio

    (University of Chieti-Pescara)

  • Sara Fontanella

    (Imperial College London)

Abstract

Recent years have seen increased attention paid to monitoring social anomie and its dependency on micro- and macro-factors. In this paper, we endorse the theorisation of social anomie as a complex, multidimensional and multilevel phenomenon. To ensure a rigorous measurement of the varying levels of social anomie in the European countries, the current study relies on a multilevel multidimensional item response theory model which explicitly accounts for the presence of a non-ignorable missing data mechanism. This unified approach makes it possible to specify an analytical model of links between anomie features and their determinants and to explore how the latent traits of interest are influenced by individual-level factors, as well as by country-level indicators. Additionally, to avoid misleading inferential conclusions, the proposed model takes into account the respondent’s omitting behaviour, assuming that the missingness mechanism is driven by a latent propensity to respond. Data used in this study have been collected in the 2010 wave of the European Social Survey. To reduce the computational complexities, a Bayesian specification of the MIRT model is provided and the parameter model estimates are obtained through MCMC algorithms.

Suggested Citation

  • Lara Fontanella & Annalina Sarra & Pasquale Valentini & Simone Zio & Sara Fontanella, 2018. "Varying levels of anomie in Europe: a multilevel analysis based on multidimensional IRT models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(4), pages 589-610, October.
  • Handle: RePEc:spr:alstar:v:102:y:2018:i:4:d:10.1007_s10182-018-0320-0
    DOI: 10.1007/s10182-018-0320-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10182-018-0320-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10182-018-0320-0?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Martijn Jong & Jan-Benedict Steenkamp, 2010. "Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research," Psychometrika, Springer;The Psychometric Society, vol. 75(1), pages 3-32, March.
    2. R. Klein Entink & J.-P. Fox & W. Linden, 2009. "A Multivariate Multilevel Approach to the Modeling of Accuracy and Speed of Test Takers," Psychometrika, Springer;The Psychometric Society, vol. 74(1), pages 21-48, March.
    3. A. Béguin & C. Glas, 2001. "MCMC estimation and some model-fit analysis of multidimensional IRT models," Psychometrika, Springer;The Psychometric Society, vol. 66(4), pages 541-561, December.
    4. Chalmers, R. Philip, 2012. "mirt: A Multidimensional Item Response Theory Package for the R Environment," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i06).
    5. Martijn G. De Jong & Jan-Benedict E. M. Steenkamp & Jean-Paul Fox, 2007. "Relaxing Measurement Invariance in Cross-National Consumer Research Using a Hierarchical IRT Model," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(2), pages 260-278, June.
    6. David Andrich, 1995. "Models for measurement, precision, and the nondichotomization of graded responses," Psychometrika, Springer;The Psychometric Society, vol. 60(1), pages 7-26, March.
    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. Lara Fontanella & Annalina Sarra & Simone Di Zio & Pasquale Valentini, 2016. "A hierarchical generalised Bayesian SEM to assess quality of democracy in Europe," METRON, Springer;Sapienza Università di Roma, vol. 74(1), pages 117-138, April.
    2. Sun-Joo Cho & Paul Boeck & Susan Embretson & Sophia Rabe-Hesketh, 2014. "Additive Multilevel Item Structure Models with Random Residuals: Item Modeling for Explanation and Item Generation," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 84-104, January.
    3. Padilla, Juan L. & Azevedo, Caio L.N. & Lachos, Victor H., 2018. "Multidimensional multiple group IRT models with skew normal latent trait distributions," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 250-268.
    4. Martijn G. de Jong & Jan-Benedict E. M. Steenkamp & Bernard P. Veldkamp, 2009. "A Model for the Construction of Country-Specific Yet Internationally Comparable Short-Form Marketing Scales," Marketing Science, INFORMS, vol. 28(4), pages 674-689, 07-08.
    5. Salzberger, Thomas & Newton, Fiona J. & Ewing, Michael T., 2014. "Detecting gender item bias and differential manifest response behavior: A Rasch-based solution," Journal of Business Research, Elsevier, vol. 67(4), pages 598-607.
    6. Chanjin Zheng & Shaoyang Guo & Justin L Kern, 2021. "Fast Bayesian Estimation for the Four-Parameter Logistic Model (4PLM)," SAGE Open, , vol. 11(4), pages 21582440211, October.
    7. Yan Huo & Jimmy de la Torre & Eun-Young Mun & Su-Young Kim & Anne Ray & Yang Jiao & Helene White, 2015. "A Hierarchical Multi-Unidimensional IRT Approach for Analyzing Sparse, Multi-Group Data for Integrative Data Analysis," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 834-855, September.
    8. Frank Rijmen & Minjeong Jeon, 2013. "Fitting an item response theory model with random item effects across groups by a variational approximation method," Annals of Operations Research, Springer, vol. 206(1), pages 647-662, July.
    9. Lara Fontanella & Paola Villano & Marika Di Donato, 2016. "Attitudes towards Roma people and migrants: a comparison through a Bayesian multidimensional IRT model," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(2), pages 471-490, March.
    10. Christopher J. Urban & Daniel J. Bauer, 2021. "A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 1-29, March.
    11. Daphna Harel & Russell J. Steele, 2018. "An Information Matrix Test for the Collapsing of Categories Under the Partial Credit Model," Journal of Educational and Behavioral Statistics, , vol. 43(6), pages 721-750, December.
    12. Tellis, Gerard J. & Chandrasekaran, Deepa, 2010. "Extent and impact of response biases in cross-national survey research," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 329-341.
    13. Wang, Luming & Finn, Adam, 2013. "Dual-faceted multidimensional IRT models with hierarchical structure," Australasian marketing journal, Elsevier, vol. 21(2), pages 111-118.
    14. Yunxiao Chen & Xiaoou Li & Siliang Zhang, 2019. "Joint Maximum Likelihood Estimation for High-Dimensional Exploratory Item Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 124-146, March.
    15. Jan-Benedict E.M. Steenkamp & Alberto Maydeu-Olivares, 2021. "An updated paradigm for evaluating measurement invariance incorporating common method variance and its assessment," Journal of the Academy of Marketing Science, Springer, vol. 49(1), pages 5-29, January.
    16. Martijn Jong & Jan-Benedict Steenkamp, 2010. "Finite Mixture Multilevel Multidimensional Ordinal IRT Models for Large Scale Cross-Cultural Research," Psychometrika, Springer;The Psychometric Society, vol. 75(1), pages 3-32, March.
    17. Izolda Pristojkovic Suko & Magdalena Holter & Erwin Stolz & Elfriede Renate Greimel & Wolfgang Freidl, 2022. "Acculturation, Adaptation, and Health among Croatian Migrants in Austria and Ireland: A Cross-Sectional Study," IJERPH, MDPI, vol. 19(24), pages 1-15, December.
    18. Nana Kim & Daniel M. Bolt & James Wollack, 2022. "Noncompensatory MIRT For Passage-Based Tests," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 992-1009, September.
    19. de Leeuw, Jan, 2006. "Principal component analysis of binary data by iterated singular value decomposition," Computational Statistics & Data Analysis, Elsevier, vol. 50(1), pages 21-39, January.
    20. Steven Andrew Culpepper & James Joseph Balamuta, 2017. "A Hierarchical Model for Accuracy and Choice on Standardized Tests," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 820-845, September.

    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:spr:alstar:v:102:y:2018:i:4:d:10.1007_s10182-018-0320-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.