Literature DB >> 12809192

Measuring behaviours and perceptions: Rasch analysis as a tool for rehabilitation research.

Luigi Tesio1.   

Abstract

Variables present in an individual, for example, independence, pain, balance, fatigue, depression and knowledge, cannot be measured directly (hence the term "latent" variables). They are usually assessed by measuring related behaviours, defined by sets of standardized items. The homogeneity of the different items, and proportionality of raw counts to measure, can only be postulated. In 1960 Georg Rasch proposed a statistical model that complied with the fundamental assumptions made in measurements in physical sciences. It allowed for the transformation of the cumulative raw scores (achieved by a subject across items, or by an item across subjects) into linear continuous measures of ability (for subjects) and difficulty (for items). These 2 parameters, only, govern the probability that "pass" rather than "fail" occurs. The discrepancies between model-expected scores (continuous between 0 and 1) and observed scores (discrete, either 0 or 1) provide indexes of inconsistency of individual subjects, items and classes of subjects. In subsequent years the same principles were extended to rating scales, with items graded on more than 2 levels, and to "many-facet" contexts where, beyond items and subjects, multiple raters, times of administration, etc. converge in determining the observed scores. Rasch modelling has increasing application in rehabilitation medicine. New scales with unprecedented metric validity (including internal consistency and reliability) can be built. Existing scales can be improved or rejected on a sound theoretical basis. In clinical trials the consistency and the linearity of measures of either subjects or raters can be validly matched with those of physical and chemical measures. The stability of the item difficulties across time, cultures, diagnostic groups and time of administration can be estimated, thus making it possible to compare homogeneous measures or foster diagnostic procedures on the reasons for differential item functioning.

Entities:  

Mesh:

Year:  2003        PMID: 12809192     DOI: 10.1080/16501970310010448

Source DB:  PubMed          Journal:  J Rehabil Med        ISSN: 1650-1977            Impact factor:   2.912


  43 in total

1.  Deriving a preference-based measure for cancer using the EORTC QLQ-C30.

Authors:  Donna Rowen; John Brazier; Tracey Young; Sabine Gaugris; Benjamin M Craig; Madeleine T King; Galina Velikova
Journal:  Value Health       Date:  2011 Jul-Aug       Impact factor: 5.725

2.  Editorial: an author's checklist for measure development and validation manuscripts.

Authors:  Grayson N Holmbeck; Katie A Devine
Journal:  J Pediatr Psychol       Date:  2009-05-31

3.  The 88-item Multiple Sclerosis Spasticity Scale: a Rasch validation of the Italian version and suggestions for refinement of the original scale.

Authors:  Leonardo Pellicciari; Marcella Ottonello; Andrea Giordano; Caterina Albensi; Franco Franchignoni
Journal:  Qual Life Res       Date:  2018-09-20       Impact factor: 4.147

4.  Psychometric properties of self-administered Lequesne Algofunctional Indexes in patients with hip and knee osteoarthritis: an evaluation using classical test theory and Rasch analysis.

Authors:  Franco Franchignoni; Fausto Salaffi; Andrea Giordano; Alessandro Ciapetti; Marina Carotti; Marcella Ottonello
Journal:  Clin Rheumatol       Date:  2011-06-14       Impact factor: 2.980

5.  Examination of the Applicability of the Disabilities of the Arm, Shoulder and Hand (DASH) Questionnaire to Patients with Hand Injuries and Diseases Using Rasch Analysis.

Authors:  Kathrin Braitmayer; Caroline Dereskewitz; Cornelia Oberhauser; Klaus-Dieter Rudolf; Michaela Coenen
Journal:  Patient       Date:  2017-06       Impact factor: 3.883

6.  Construct validity of the Eating Assessment Tool (EAT-10).

Authors:  Janina Wilmskoetter; Heather Bonilha; Ickpyo Hong; R Jordan Hazelwood; Bonnie Martin-Harris; Craig Velozo
Journal:  Disabil Rehabil       Date:  2017-11-09       Impact factor: 3.033

Review 7.  The Role of Condition-Specific Preference-Based Measures in Health Technology Assessment.

Authors:  Donna Rowen; John Brazier; Roberta Ara; Ismail Azzabi Zouraq
Journal:  Pharmacoeconomics       Date:  2017-12       Impact factor: 4.981

8.  Leisure repertoire among persons with a spinal cord injury: interests, performance, and well-being.

Authors:  Ulrica Lundström; Margareta Lilja; Ingela Petersson; Jan Lexell; Gunilla Isaksson
Journal:  J Spinal Cord Med       Date:  2013-11-26       Impact factor: 1.985

9.  Use of Rasch methodology to develop a short version of the health related quality of life for eating disorders questionnaire: a prospective study.

Authors:  Carlota Las Hayas; Jose M Quintana; Jesús A Padierna; Amaia Bilbao; Pedro Muñoz
Journal:  Health Qual Life Outcomes       Date:  2010-03-18       Impact factor: 3.186

10.  Measuring stroke survivors' functional status independence: five perspectives.

Authors:  Min-Mei Shih; Joan C Rogers; Elizabeth R Skidmore; James J Irrgang; Margo B Holm
Journal:  Am J Occup Ther       Date:  2009 Sep-Oct
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.