A System for Managing the Quality of Official Statistics
Author
Abstract
Suggested Citation
DOI: 10.2478/jos-2014-0022
Download full text from publisher
References listed on IDEAS
- Ron S. Kenett & Galit Shmueli, 2014. "On information quality," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(1), pages 3-38, January.
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.- Pierpaolo D’Urso & Vincenzina Vitale, 2020. "Bayesian Networks Model Averaging for Bes Indicators," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 151(3), pages 897-919, October.
- Pierpaolo D’Urso & Vincenzina Vitale, 2021. "Modeling Local BES Indicators by Copula-Based Bayesian Networks," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 153(3), pages 823-847, February.
- Federica Cugnata & Silvia Salini, 2014. "Model-based approach for importance–performance analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3053-3064, November.
- Coleman Shirley Y., 2016. "Data-Mining Opportunities for Small and Medium Enterprises with Official Statistics in the UK," Journal of Official Statistics, Sciendo, vol. 32(4), pages 849-865, December.
- Domenico Piccolo & Rosaria Simone, 2019. "Rejoinder to the discussion of “The class of cub models: statistical foundations, inferential issues and empirical evidence”," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 477-493, September.
- Galit Shmueli, 2020. "Discussion on “Assessing the goodness of fit of logistic regression models in large samples: A modification of the Hosmer‐Lemeshow test” by Giovanni Nattino, Michael L. Pennell, and Stanley Lemeshow," Biometrics, The International Biometric Society, vol. 76(2), pages 561-563, June.
- Paola Zola & Paulo Cortez & Costantino Ragno & Eugenio Brentari, 2019. "Social Media Cross-Source and Cross-Domain Sentiment Classification," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(05), pages 1469-1499, September.
- Inbal Yahav & Galit Shmueli, 2014. "Outcomes matter: estimating pre-transplant survival rates of kidney-transplant patients using simulator-based propensity scores," Annals of Operations Research, Springer, vol. 216(1), pages 101-128, May.
- Kenett Ron S. & Shmueli Galit, 2016. "From Quality to Information Quality in Official Statistics," Journal of Official Statistics, Sciendo, vol. 32(4), pages 867-885, December.
- Ruojing Zhang & Marta Indulska & Shazia Sadiq, 2019. "Discovering Data Quality Problems," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(5), pages 575-593, October.
- Ron S. Kenett & Abraham Rubinstein, 2021. "Generalizing research findings for enhanced reproducibility: an approach based on verbal alternative representations," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4137-4151, May.
- Rosaria Simone, 2023. "Uncertainty Diagnostics of Binomial Regression Trees for Ordered Rating Data," Journal of Classification, Springer;The Classification Society, vol. 40(1), pages 79-105, April.
- Mahsa Ashouri & Kate Cai & Furen Lin & Galit Shmueli, 2018. "Assessing the Value of an Information System for Developing Predictive Analytics: The Case of Forecasting School-Level Demand in Taiwan," Service Science, INFORMS, vol. 10(1), pages 58-75, March.
- Nikolaos Askitas, 2016.
"Big Data is a big deal but how much data do we need? [Big Data gut und schön. Aber wie viel Data brauchen wir?],"
AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(2), pages 113-125, October.
- Askitas, Nikos, 2016. "Big Data Is a Big Deal But How Much Data Do We Need?," IZA Discussion Papers 9988, Institute of Labor Economics (IZA).
More about this item
Keywords
Total survey error; process control; GDP; quality indicators; statistical standards;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:vrs:offsta:v:30:y:2014:i:3:p:35:n:1. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.