IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v59y2003i1p189-196.html
   My bibliography  Save this article

Latent Class Model Diagnosis from a Frequentist Point of View

Author

Listed:
  • Anton K. Formann

Abstract

No abstract is available for this item.

Suggested Citation

  • Anton K. Formann, 2003. "Latent Class Model Diagnosis from a Frequentist Point of View," Biometrics, The International Biometric Society, vol. 59(1), pages 189-196, March.
  • Handle: RePEc:bla:biomet:v:59:y:2003:i:1:p:189-196
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/1541-0420.00023
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. C. Dayton & George Macready, 1980. "A scaling model with response errors and intrinsically unscalable respondents," Psychometrika, Springer;The Psychometric Society, vol. 45(3), pages 343-356, September.
    2. Richard McHugh, 1958. "Note on “efficient estimation and local identification in latent class analysis”," Psychometrika, Springer;The Psychometric Society, vol. 23(3), pages 273-274, September.
    3. Jan De Leeuw & Norman Verhelst, 1986. "Maximum Likelihood Estimation in Generalized Rasch Models," Journal of Educational and Behavioral Statistics, , vol. 11(3), pages 183-196, September.
    4. Anton K. Formann & Thomas Kohlmann, 1998. "Structural Latent Class Models," Sociological Methods & Research, , vol. 26(4), pages 530-565, May.
    5. Richard McHugh, 1956. "Efficient estimation and local identification in latent class analysis," Psychometrika, Springer;The Psychometric Society, vol. 21(4), pages 331-347, December.
    6. C. Proctor, 1970. "A probabilistic formulation and statistical analysis of guttman scaling," Psychometrika, Springer;The Psychometric Society, vol. 35(1), pages 73-78, March.
    7. Elizabeth S. Garrett & Scott L. Zeger, 2000. "Latent Class Model Diagnosis," Biometrics, The International Biometric Society, vol. 56(4), pages 1055-1067, December.
    8. Anders Christoffersson, 1975. "Factor analysis of dichotomized variables," Psychometrika, Springer;The Psychometric Society, vol. 40(1), pages 5-32, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Baffour Bernard & Brown James J. & Smith Peter W.F., 2021. "Latent Class Analysis for Estimating an Unknown Population Size – with Application to Censuses," Journal of Official Statistics, Sciendo, vol. 37(3), pages 673-697, September.
    2. Patrício Soares Costa & Nadine Correia Santos & Pedro Cunha & Joana Almeida Palha & Nuno Sousa, 2013. "The Use of Bayesian Latent Class Cluster Models to Classify Patterns of Cognitive Performance in Healthy Ageing," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-8, August.
    3. Aurélie Bertrand & Christian Hafner, 2014. "On heterogeneous latent class models with applications to the analysis of rating scores," Computational Statistics, Springer, vol. 29(1), pages 307-330, February.
    4. van Wieringen, Wessel N., 2005. "On identifiability of certain latent class models," Statistics & Probability Letters, Elsevier, vol. 75(3), pages 211-218, December.
    5. Formann, Anton K., 2007. "Mixture analysis of multivariate categorical data with covariates and missing entries," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5236-5246, July.

    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. Beth A. Reboussin & Nicholas S. Ialongo, 2010. "Latent transition models with latent class predictors: attention deficit hyperactivity disorder subtypes and high school marijuana use," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 145-164, January.
    2. Anton K. Formann & Thomas Kohlmann, 1998. "Structural Latent Class Models," Sociological Methods & Research, , vol. 26(4), pages 530-565, May.
    3. Alberto Maydeu-Olivares & Rosa Montaño, 2013. "How Should We Assess the Fit of Rasch-Type Models? Approximating the Power of Goodness-of-Fit Statistics in Categorical Data Analysis," Psychometrika, Springer;The Psychometric Society, vol. 78(1), pages 116-133, January.
    4. Jesus Perez-Mayo, 2005. "Identifying deprivation profiles in Spain: a new approach," Applied Economics, Taylor & Francis Journals, vol. 37(8), pages 943-955.
    5. Enzo Loner, 2016. "A new way of looking at old things. An application of Guttman errors analysis to the study of environmental concern," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(2), pages 823-847, March.
    6. Yang Yixin & Lü Xin & Ma Jian & Qiao Han, 2014. "A Robust Factor Analysis Model for Dichotomous Data," Journal of Systems Science and Information, De Gruyter, vol. 2(5), pages 437-450, October.
    7. Beth A. Reboussin & Edward H. Ip & Mark Wolfson, 2008. "Locally dependent latent class models with covariates: an application to under‐age drinking in the USA," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(4), pages 877-897, October.
    8. Edward Haertel, 1990. "Continuous and discrete latent structure models for item response data," Psychometrika, Springer;The Psychometric Society, vol. 55(3), pages 477-494, September.
    9. Yan Feng & Erpeng Liu & Zhang Yue & Qilin Zhang & Tiankuo Han, 2019. "The Evolutionary Trends of Health Behaviors in Chinese Elderly and the Influencing Factors of These Trends: 2005–2014," IJERPH, MDPI, vol. 16(10), pages 1-17, May.
    10. Leonard J. Paas & Jeroen K. Vermunt & Tammo H. A. Bijmolt, 2007. "Discrete time, discrete state latent Markov modelling for assessing and predicting household acquisitions of financial products," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(4), pages 955-974, October.
    11. Fabrizia Mealli & Barbara Pacini & Elena Stanghellini, 2016. "Identification of Principal Causal Effects Using Additional Outcomes in Concentration Graphs," Journal of Educational and Behavioral Statistics, , vol. 41(5), pages 463-480, October.
    12. Michel Wedel & Wayne DeSarbo, 1995. "A mixture likelihood approach for generalized linear models," Journal of Classification, Springer;The Classification Society, vol. 12(1), pages 21-55, March.
    13. Korner-Nievergelt, Fränzi & Prévot, Céline & Hahn, Steffen & Jenni, Lukas & Liechti, Felix, 2017. "The integration of mark re-encounter and tracking data to quantify migratory connectivity," Ecological Modelling, Elsevier, vol. 344(C), pages 87-94.
    14. Hwan Chung & Brian P. Flaherty & Joseph L. Schafer, 2006. "Latent class logistic regression: application to marijuana use and attitudes among high school seniors," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 723-743, October.
    15. Yun Li & Jeremy M.G. Taylor & Michael R. Elliott, 2010. "A Bayesian Approach to Surrogacy Assessment Using Principal Stratification in Clinical Trials," Biometrics, The International Biometric Society, vol. 66(2), pages 523-531, June.
    16. Lin Ting Hsiang, 2006. "A comparison of model selection indices for nested latent class models," Monte Carlo Methods and Applications, De Gruyter, vol. 12(3), pages 239-259, October.
    17. repec:jss:jstsof:37:i02 is not listed on IDEAS
    18. Frank Rijmen & Paul De Boeck, 2005. "A relation between a between-item multidimensional IRT model and the mixture rasch model," Psychometrika, Springer;The Psychometric Society, vol. 70(3), pages 481-496, September.
    19. Adam Carle, 2010. "Interpreting the results of studies using latent variable models to assess data quality: an empirical example using confirmatory factor analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(3), pages 483-497, April.
    20. Albert Maydeu-Olivares & Harry Joe, 2006. "Limited Information Goodness-of-fit Testing in Multidimensional Contingency Tables," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 713-732, December.
    21. C. Dayton & George Macready, 1980. "A scaling model with response errors and intrinsically unscalable respondents," Psychometrika, Springer;The Psychometric Society, vol. 45(3), pages 343-356, September.

    More about this item

    Statistics

    Access and download statistics

    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:bla:biomet:v:59:y:2003:i:1:p:189-196. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.