Congenial Multiple Imputation and Matched Pairs Models for Square Tables: An Example of patients¡¯ self-management
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Yucel, Recai M., 2011. "State of the Multiple Imputation Software," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i01).
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.- Martin, Eisele & Zhu, Junyi, 2013.
"Multiple imputation in a complex household survey - the German Panel on Household Finances (PHF): challenges and solutions,"
MPRA Paper
57666, University Library of Munich, Germany.
- Eisele, Martin & Zhu, Junyi, 2013. "Multiple imputation in a complex household survey - the German Panel on Household Finances (PHF): challenges and solutions," EconStor Preprints 100007, ZBW - Leibniz Information Centre for Economics.
- Florian M. Hollenbach & Iavor Bojinov & Shahryar Minhas & Nils W. Metternich & Michael D. Ward & Alexander Volfovsky, 2021. "Multiple Imputation Using Gaussian Copulas," Sociological Methods & Research, , vol. 50(3), pages 1259-1283, August.
- Josse, Julie & Husson, François, 2016. "missMDA: A Package for Handling Missing Values in Multivariate Data Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 70(i01).
- Yajuan Si & Roderick J. A. Little & Ya Mo & Nell Sedransk, 2023. "A Case Study of Nonresponse Bias Analysis in Educational Assessment Surveys," Journal of Educational and Behavioral Statistics, , vol. 48(3), pages 271-295, June.
- Schalk Burger & Searle Silverman & Gary van Vuuren, 2018. "Deriving Correlation Matrices for Missing Financial Time-Series Data," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(10), pages 105-105, October.
- Celeste Combrinck & Vanessa Scherman & David Maree & Sarah Howie, 2018. "Multiple Imputation for Dichotomous MNAR Items Using Recursive Structural Equation Modeling With Rasch Measures as Predictors," SAGE Open, , vol. 8(1), pages 21582440187, February.
- Rüdiger Mutz & Lutz Bornmann & Hans-Dieter Daniel, 2015. "Testing for the fairness and predictive validity of research funding decisions: A multilevel multiple imputation for missing data approach using ex-ante and ex-post peer evaluation data from the Austr," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2321-2339, November.
More about this item
JEL classification:
- R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
- Z0 - Other Special Topics - - General
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:jfr:jbar11:v:2:y:2013:i:1:p:1-8. 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: Grace Lee (email available below). General contact details of provider: http://jbar.sciedupress.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.