The object detection logic of latent variable technologies
Author
Abstract
Suggested Citation
DOI: 10.1007/s11135-015-0303-0
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Stanley Mulaik, 1976. "Comments on “the measurement of factorial indeterminacy”," Psychometrika, Springer;The Psychometric Society, vol. 41(2), pages 249-262, June.
- Paul Holland, 1990. "On the sampling theory roundations of item response theory models," Psychometrika, Springer;The Psychometric Society, vol. 55(4), pages 577-601, December.
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.- Willem E. Saris & Marius de Pijper & Jan Mulder, 1978. "Optimal Procedures for Estimation of Factor Scores," Sociological Methods & Research, , vol. 7(1), pages 85-106, August.
- Robitzsch, Alexander, 2020. "About Still Nonignorable Consequences of (Partially) Ignoring Missing Item Responses in Large-scale Assessment," OSF Preprints hmy45, Center for Open Science.
- Kohei Adachi & Nickolay T. Trendafilov, 2018. "Some Mathematical Properties of the Matrix Decomposition Solution in Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 83(2), pages 407-424, June.
- Pascal Jordan & Martin Spiess, 2012. "Generalizations of Paradoxical Results in Multidimensional Item Response Theory," Psychometrika, Springer;The Psychometric Society, vol. 77(1), pages 127-152, January.
- Paula Fariña & Jorge González & Ernesto San Martín, 2019. "The Use of an Identifiability-Based Strategy for the Interpretation of Parameters in the 1PL-G and Rasch Models," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 511-528, June.
- Anders Skrondal & Sophia Rabe-Hesketh, 2022. "The Role of Conditional Likelihoods in Latent Variable Modeling," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 799-834, September.
- Stefano Noventa & Luca Stefanutti & Giulio Vidotto, 2014. "An Analysis of Item Response Theory and Rasch Models Based on the Most Probable Distribution Method," Psychometrika, Springer;The Psychometric Society, vol. 79(3), pages 377-402, July.
- Jules L. Ellis, 2021. "A Test Can Have Multiple Reliabilities," Psychometrika, Springer;The Psychometric Society, vol. 86(4), pages 869-876, December.
- Chen, Yunxiao & Li, Xiaoou & Zhang, Siliang, 2019. "Structured latent factor analysis for large-scale data: identifiability, estimability, and their implications," LSE Research Online Documents on Economics 101122, London School of Economics and Political Science, LSE Library.
- Klaas Sijtsma & Julius M. Pfadt, 2021. "Rejoinder: The Future of Reliability," Psychometrika, Springer;The Psychometric Society, vol. 86(4), pages 887-892, December.
- Ting Lin, 2007. "Identifying Optimal Items in Quality of Life Assessment," Quality & Quantity: International Journal of Methodology, Springer, vol. 41(5), pages 661-672, October.
- Ting Lin & Grace Yao, 2009. "Evaluating Item Discrimination Power of WHOQOL-BREF from an Item Response Model Perspectives," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 91(2), pages 141-153, April.
- Merton S. Krause, 2017. "Item response theory requires logically unjustifiable assumptions," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(4), pages 1549-1561, July.
- Kohei Uno & Kohei Adachi & Nickolay T. Trendafilov, 2019. "Clustered Common Factor Exploration in Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 84(4), pages 1048-1067, December.
- Sandip Sinharay & Paul Holland, 2010. "The Missing Data Assumptions of the NEAT Design and their Implications for Test Equating," Psychometrika, Springer;The Psychometric Society, vol. 75(2), pages 309-327, June.
- Ganglmair-Wooliscroft, Alexandra & Wooliscroft, Ben, 2016. "Diffusion of innovation: The case of ethical tourism behavior," Journal of Business Research, Elsevier, vol. 69(8), pages 2711-2720.
More about this item
Keywords
Latent variable models; Object detection; Latent structure detection;All these keywords.
Statistics
Access and download statisticsCorrections
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:qualqt:v:51:y:2017:i:1:d:10.1007_s11135-015-0303-0. 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.