Mapping the Paediatric Quality of Life Inventory (PedsQL™) Generic Core Scales onto the Child Health Utility Index–9 Dimension (CHU-9D) Score for Economic Evaluation in Children
Author
Abstract
Suggested Citation
DOI: 10.1007/s40273-017-0600-7
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
- Brazier, John & Ratcliffe, Julie & Salomon, Joshua & Tsuchiya, Aki, 2016.
"Measuring and Valuing Health Benefits for Economic Evaluation,"
OUP Catalogue,
Oxford University Press,
edition 2, number 9780198725923.
- Brazier, John & Ratcliffe, Julie & Salomon, Joshua A. & Tsuchiya, Aki, 2007. "Measuring and Valuing Health Benefits for Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198569824.
- Christine Mpundu-Kaambwa & Gang Chen & Remo Russo & Katherine Stevens & Karin Dam Petersen & Julie Ratcliffe, 2017. "Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15," PharmacoEconomics, Springer, vol. 35(4), pages 453-467, April.
- Reynolds, Anderson & Shonkwiler, J S, 1991. "Testing and Correcting for Distributional Misspecifications in the Tobit Model: An Application of the Information Matrix Test," Empirical Economics, Springer, vol. 16(3), pages 313-323.
- Ratcliffe, Julie & Huynh, Elisabeth & Chen, Gang & Stevens, Katherine & Swait, Joffre & Brazier, John & Sawyer, Michael & Roberts, Rachel & Flynn, Terry, 2016. "Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm," Social Science & Medicine, Elsevier, vol. 157(C), pages 48-59.
- Hyndman, Rob J. & Koehler, Anne B., 2006.
"Another look at measures of forecast accuracy,"
International Journal of Forecasting, Elsevier, vol. 22(4), pages 679-688.
- Rob J. Hyndman & Anne B. Koehler, 2005. "Another Look at Measures of Forecast Accuracy," Monash Econometrics and Business Statistics Working Papers 13/05, Monash University, Department of Econometrics and Business Statistics.
- Karen Gerard & Gavin Mooney, 1993. "Qaly league tables: Handle with care," Health Economics, John Wiley & Sons, Ltd., vol. 2(1), pages 59-64, April.
- Erik Nord, 1994. "The qaly—a measure of social value rather than individual utility?," Health Economics, John Wiley & Sons, Ltd., vol. 3(2), pages 89-93, March.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Chris Sampson;Martina Garau, 2019. "How Should We Measure Quality of Life Impact in Rare Disease? Recent Learnings in Spinal Muscular Atrophy," Briefing 002146, Office of Health Economics.
- Christine Mpundu-Kaambwa & Gang Chen & Elisabeth Huynh & Remo Russo & Julie Ratcliffe, 2019. "Mapping the PedsQL™ onto the CHU9D: An Assessment of External Validity in a Large Community-Based Sample," PharmacoEconomics, Springer, vol. 37(9), pages 1139-1153, September.
- Asrul Akmal Shafie & Irwinder Kaur Chhabra & Jacqueline Hui Yi Wong & Noor Syahireen Mohammed, 2021. "Mapping PedsQL™ Generic Core Scales to EQ-5D-3L utility scores in transfusion-dependent thalassemia patients," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(5), pages 735-747, 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.- Karin Dam Petersen & Gang Chen & Christine Mpundu-Kaambwa & Katherine Stevens & John Brazier & Julie Ratcliffe, 2018. "Measuring Health-Related Quality of Life in Adolescent Populations: An Empirical Comparison of the CHU9D and the PedsQLTM 4.0 Short Form 15," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 11(1), pages 29-37, February.
- John Hutton, 2012. "‘Health Economics’ and the evolution of economic evaluation of health technologies," Health Economics, John Wiley & Sons, Ltd., vol. 21(1), pages 13-18, January.
- Valentina Prevolnik Rupel & Marko Ogorevc, 2021. "EQ-5D-Y Value Set for Slovenia," PharmacoEconomics, Springer, vol. 39(4), pages 463-471, April.
- Christine Mpundu-Kaambwa & Gang Chen & Remo Russo & Katherine Stevens & Karin Dam Petersen & Julie Ratcliffe, 2017. "Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15," PharmacoEconomics, Springer, vol. 35(4), pages 453-467, April.
- repec:prg:jnlcfu:v:2022:y:2022:i:1:id:572 is not listed on IDEAS
- Joanna M Charles & Deirdre M Harrington & Melanie J Davies & Charlotte L Edwardson & Trish Gorely & Danielle H Bodicoat & Kamlesh Khunti & Lauren B Sherar & Thomas Yates & Rhiannon Tudor Edwards, 2019. "Micro-costing and a cost-consequence analysis of the ‘Girls Active’ programme: A cluster randomised controlled trial," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-17, August.
- Chang, Andrew C. & Hanson, Tyler J., 2016. "The accuracy of forecasts prepared for the Federal Open Market Committee," Journal of Economics and Business, Elsevier, vol. 83(C), pages 23-43.
- Frank, Johannes, 2023. "Forecasting realized volatility in turbulent times using temporal fusion transformers," FAU Discussion Papers in Economics 03/2023, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
- Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
- Paulo Júlio & Pedro M. Esperança, 2012. "Evaluating the forecast quality of GDP components: An application to G7," GEE Papers 0047, Gabinete de Estratégia e Estudos, Ministério da Economia, revised Apr 2012.
- Cameron Roach & Rob Hyndman & Souhaib Ben Taieb, 2021.
"Non‐linear mixed‐effects models for time series forecasting of smart meter demand,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 1118-1130, September.
- Cameron Roach & Rob J Hyndman & Souhaib Ben Taieb, 2020. "Nonlinear Mixed Effects Models for Time Series Forecasting of Smart Meter Demand," Monash Econometrics and Business Statistics Working Papers 41/20, Monash University, Department of Econometrics and Business Statistics.
- Alysha M De Livera, 2010. "Automatic forecasting with a modified exponential smoothing state space framework," Monash Econometrics and Business Statistics Working Papers 10/10, Monash University, Department of Econometrics and Business Statistics.
- Nikitopoulos, Christina Sklibosios & Thomas, Alice Carole & Wang, Jianxin, 2023. "The economic impact of daily volatility persistence on energy markets," Journal of Commodity Markets, Elsevier, vol. 30(C).
- Stevens, K, 2010. "Valuation of the Child Health Utility Index 9D (CHU9D)," MPRA Paper 29938, University Library of Munich, Germany.
- I. Yu. Zolotova & V. V. Dvorkin, 2017. "Short-term forecasting of prices for the Russian wholesale electricity market based on neural networks," Studies on Russian Economic Development, Springer, vol. 28(6), pages 608-615, November.
- Döpke, Jörg & Fritsche, Ulrich & Müller, Karsten, 2019. "Has macroeconomic forecasting changed after the Great Recession? Panel-based evidence on forecast accuracy and forecaster behavior from Germany," Journal of Macroeconomics, Elsevier, vol. 62(C).
- Steven Yen, 1995. "Alternative transformations in a class of limited dependent variable models: alcohol consumption by US women," Applied Economics Letters, Taylor & Francis Journals, vol. 2(8), pages 258-262.
- Thiyanga S. Talagala & Feng Li & Yanfei Kang, 2019. "Feature-based Forecast-Model Performance Prediction," Monash Econometrics and Business Statistics Working Papers 21/19, Monash University, Department of Econometrics and Business Statistics.
- Brazier, JE & Yang, Y & Tsuchiya, A, 2008. "A review of studies mapping (or cross walking) from non-preference based measures of health to generic preference-based measures," MPRA Paper 29808, University Library of Munich, Germany.
- Martin Guth, 2022. "Predicting Default Probabilities for Stress Tests: A Comparison of Models," Papers 2202.03110, arXiv.org.
- Santamaría-Bonfil, G. & Reyes-Ballesteros, A. & Gershenson, C., 2016. "Wind speed forecasting for wind farms: A method based on support vector regression," Renewable Energy, Elsevier, vol. 85(C), pages 790-809.
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:pharme:v:36:y:2018:i:4:d:10.1007_s40273-017-0600-7. 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.