Rasch analysis of the Roland-Morris Disability Questionnaire Megan Davidson, PhD School of Physiotherapy, La Trobe University, Melbourne.

Slides:



Advertisements
Similar presentations
Questionnaire Development
Advertisements

Deciding which statistical test to use:. Tests covered on this course: (a) Nonparametric tests: Frequency data - Chi-Square test of association between.
Psychometrics to Support RtI Assessment Design Michael C. Rodriguez University of Minnesota February 2010.
Item Response Theory in a Multi-level Framework Saralyn Miller Meg Oliphint EDU 7309.
Children’s subjective well-being Findings from national surveys in England International Society for Child Indicators Conference, 27 th July 2011.
Item Response Theory in Health Measurement
There is a need to validate existing patient reported outcome measures (PROMS) to provide evidence on their validity. Subsequently, short measures can.
Overview of field trial analysis procedures National Research Coordinators Meeting Windsor, June 2008.
Health-related quality of life in diabetic patients and controls without diabetes in refugee camps in Gaza strip: a cross-sectional study By: Ashraf Eljedi:
Item Response Theory. Shortcomings of Classical True Score Model Sample dependence Limitation to the specific test situation. Dependence on the parallel.
Hypothesis Testing. G/RG/R Null Hypothesis: The means of the populations from which the samples were drawn are the same. The samples come from the same.
UNDERSTANDING RESEARCH RESULTS: STATISTICAL INFERENCE © 2012 The McGraw-Hill Companies, Inc.
Richard M. Jacobs, OSA, Ph.D.
Multivariate Methods EPSY 5245 Michael C. Rodriguez.
1 Reducing the duration and cost of assessment with the GAIN: Computer Adaptive Testing.
Measurement Problems within Assessment: Can Rasch Analysis help us? Mike Horton Bipin Bhakta Alan Tennant.
        Analysis of Preschool Assessment Data Desired Results Development Profile Preschool © DRDP – PS (2010)       Ifthika “Shine” Nissar, M.A.
Item Response Theory for Survey Data Analysis EPSY 5245 Michael C. Rodriguez.
Reporting item response theory results Jeffrey B. Brookings Wittenberg University Presented at the SAMR/SWPA Symposium: Handy tips for communicating and.
Measuring the Psychosocial Quality of Women’s Family Work: Initial Findings Tamara Colton 1 BA (Hons), Laurie Hellsten 1 PhD & Bonnie Janzen 2 PhD 1 Department.
Lecture 7 Chapter 7 – Correlation & Differential (Quasi)
Instrumentation.
McMillan Educational Research: Fundamentals for the Consumer, 6e © 2012 Pearson Education, Inc. All rights reserved. Educational Research: Fundamentals.
Chapter Eight The Concept of Measurement and Attitude Scales
Variable  An item of data  Examples: –gender –test scores –weight  Value varies from one observation to another.
Introduction ANOVA Mike Tucker School of Psychology B209 Portland Square University of Plymouth Drake Circus Plymouth, PL4 8AA Tel: +44 (0)
Instrumentation (cont.) February 28 Note: Measurement Plan Due Next Week.
Possible Selves of New Zealanders: An examination of the Hopes and Fears of young New Zealanders. Presented by Paul Englert.
Developing a Tool to Measure Health Worker Motivation in District Hospitals in Kenya Patrick Mbindyo, Duane Blaauw, Lucy Gilson, Mike English.
Counseling Research: Quantitative, Qualitative, and Mixed Methods, 1e © 2010 Pearson Education, Inc. All rights reserved. Basic Statistical Concepts Sang.
Mearns (1996, 1997) - an extension of Rogers’ (1957) facilitative conditions of therapeutic change. Mearns (2003) - serves as a distinctive hallmark of.
Table 2: Correlation between age and readiness to change Table 1: T-test relating gender and readiness to change  It is estimated that 25% of children.
Experiment Basics: Variables Psych 231: Research Methods in Psychology.
Descriptive Research Study Investigation of Positive and Negative Affect of UniJos PhD Students toward their PhD Research Project Dr. K. A. Korb University.
Educational Research Chapter 13 Inferential Statistics Gay, Mills, and Airasian 10 th Edition.
Chapter 2: Behavioral Variability and Research Variability and Research 1. Behavioral science involves the study of variability in behavior how and why.
1 Task Force on Health Expectancies National Disability Survey and Sport and Physical Exercise Module Gerry Brady Central Statistics Office, Ireland Luxembourg.
Item Response Theory (IRT) Models for Questionnaire Evaluation: Response to Reeve Ron D. Hays October 22, 2009, ~3:45-4:05pm
Examining Data. Constructing a variable 1. Assemble a set of items that might work together to define a construct/ variable. 2. Hypothesize the hierarchy.
Multitrait Scaling and IRT: Part I Ron D. Hays, Ph.D. Questionnaire Design and Testing.
Psychometrics. Goals of statistics Describe what is happening now –DESCRIPTIVE STATISTICS Determine what is probably happening or what might happen in.
Reliability and validity of the adapted Spanish version of the Early Onset Scoliosis-24 questionnaire María del Mar Pozo-Balado, PhD Hiroko Matsumoto PhD.
IMPORTANCE OF STATISTICS MR.CHITHRAVEL.V ASST.PROFESSOR ACN.
Correlation They go together like salt and pepper… like oil and vinegar… like bread and butter… etc.
The Quality of Life Index A Literature Survey of the Usage and Results from the Ferrans and Powers QLI.
Reliability: Introduction. Reliability Session 1.Definitions & Basic Concepts of Reliability 2.Theoretical Approaches 3.Empirical Assessments of Reliability.
Item Response Theory in Health Measurement
FIT ANALYSIS IN RASCH MODEL University of Ostrava Czech republic 26-31, March, 2012.
Mary K. Anthony, PhD,RN 1,2 Kathleen Vidal, MSN,RN 2 Pimpanitta Jittapiriom, PhD (candidate) 1 Carolyn Kleman, MSN, RN 1 Amany Farag, PhD,RN 3 Supported.
Most common nursing care problems: a national survey Renate Kieft, PhD student Tilburg University and advisor Dutch Nurses’ Association 31 januari 2016Dutch.
6 Indexes, Scales, and Typologies Indexes Vs. Scales ◦ indexes are different than scales ◦ both are composite measures ◦ indexes are simply summed ◦ scales.
Reliability a measure is reliable if it gives the same information every time it is used. reliability is assessed by a number – typically a correlation.
Konrad Pesudovs, Vijaya Gothwal, Thomas Wright, David Elliott
Considerations in Comparing Groups of People with PROs Ron D. Hays, Ph.D. UCLA Department of Medicine May 6, 2008, 3:45-5:00pm ISPOR, Toronto, Canada.
Item Response Theory Dan Mungas, Ph.D. Department of Neurology University of California, Davis.
Discussion of Issues and Approaches Presented by Templin and Teresi
Psychometrics: Exam Analysis David Hope
Interpretation of Common Statistical Tests Mary Burke, PhD, RN, CNE.
Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins Chapter 11 Measurement and Data Quality.
The Impact of Lifestyle Modification on the Health-Related Quality of Life of Patients With Reflux Esophagitis Receiving Treatment With a Proton Pump Inhibitor.
UCLA Department of Medicine
UCLA Department of Medicine
assessing scale reliability
Spearman’s rho Chi-square (χ2)
Reliability, validity, and scaling
2UNIVERSITY OF WATERLOO
EPSY 5245 EPSY 5245 Michael C. Rodriguez
15.1 The Role of Statistics in the Research Process
Examining Data.
Evaluating Multi-item Scales
Presentation transcript:

Rasch analysis of the Roland-Morris Disability Questionnaire Megan Davidson, PhD School of Physiotherapy, La Trobe University, Melbourne

Questionnaires Functioning Disability Ability Health status Activity limitations Participation restrictions Quality of life Well being Level of assistance Typically have n items summed to give a total score Higher score indicates more or less of the “thing” being measured

The scores are ordinal Rank order Distance between ranks is unknown Distance between adjacent scores are not equivalent units Arguably, ordinal scores cannot be manipulated mathematically

How far will the cars go? 4 cars are filled with petrol to see how far they go on a full tank of fuel. 3 observers are positioned along the route.

Green: Score 3 Blue: Score 2 Red: Score 2 Yellow: Score 1

Rasch analysis Modern Test Theory (Item response) Models the probability that a person of θ ability will be able to do activity of δ difficulty Locates item difficulty and person ability on an interval-level logit scale Logit = log-odds unit probability a person can perform the task divided by the probability they cannot

Advantage of Rasch modelling Measure what is measurable, and make measurable what is not so. (Galileo Galilei) “Rasch… provides an operational criterion for fundamental measurement of the kind found in the physical sciences” David Andrich

Easy activities Hard activities Least able person Most able person Get out of bedHouseworkGardeningSport

Roland-Morris Questionnaire (RDQ) A low-back specific disability questionnaire 24-items from the Sickness Impact Profile Patient self-completed Tick those that apply “today” Number of items selected = score Possible score 0-24 Higher score indicates greater disability

Roland-Morris Disability Questionnaire 1. I stay at home most of the time because of my back 2. I change position frequently to try and get my back comfortable 3. I walk more slowly than usual because of my back 4. Because of my back, I am not doing any of the jobs that I usually do around the house

RDQ content housework self-care walking sleeping sitting irritability appetite pain

Short-form versions RDQ 18-item version Stratford & Binkley item version Williams & Myers 2001

Classical (Traditional) Test Theory Reject/retain items on some basis Very low or high response frequency Very low or high item-item correlations Low or high corrected item-total correlations Cronbach’s alpha in range considered desirable

18-item versions Stratford & Binkley Response frequency 90% Item-item correlations > 0.75 Item-total correlations <.40 Increased Cronbach’s alpha Williams & Myer Response frequency 80% Item-item correlations > 0.75 Item-total correlations <.20 Cronbach’s alpha >.80

Items removed in 18-item versions Stratford & Binkley 2 change position 15 appetite not good 17 walk short distance 19 dress with help 20 sit most of day 24 stay in bed Williams & Myers 2 change position 15 appetite not good 19 dress with help 20 sit most of day 22 more irritable 24 stay in bed

Aim: To examine fit to a Rasch model of the 24- item and two 18-item versions of the RDQ To explore whether decisions to reject items on the basis of Rasch analysis would differ from that made by the developers of two 18- item versions of the RDQ.

Is RDQ unidimensional? Items drawn from several SIP domains Williams & Myers 2001 Many low item-item and some low item-total correlations 4 factors explaining 55% of total variance

Method Data for 140 people from a previous study Battery of questionnaires including RDQ Participants were seeking physiotherapy treatment for a low back problem aged 18 years or older read and write English. Recruited from public hospitals, community health centres and private practices. RUMM2020 Rasch analysis software

Results (n = 140) Mean age 51 years (sd 17, range 18-89) 66% female 41% employed 43% pain < 6 weeks 34% pain > 6 months 70% pain that referred into the buttock or leg. RDQ score 9 (sd 5.6), median 8 (IQR 5-14).

Item-Trait Interaction Item Fit Residual Item Fit  2 and F-stat PSI 24-item RDQ (-2.47) 17 (-2.28) 22 (2.19)  2 p all >.01 F 17 p = item Stratford (-2.41)  2 p all >.01 F 9 p = item Williams (-2.18) 17 (-2.15) 18 (2.22)  2 p all >.01 F 17 p = Poor fit if item-trait p ±2,  2 p <.01, F p <.01 PSI = Person Separation Index COMPARISON OF FIT TO THE RASCH MODEL

Differential Item Functioning (DIF) An item may attract systematically different responses on the basis of some characteristic other than item difficulty Age Gender DIF by age and gender in all versions Item 5 Because of my back, I use a handrail to get upstairs

Which items would Rasch reject? 17 walk short distances 9 dress slowly Negative residuals indicate redundancy 5 use handrail upstairs DIF by age/gender 16 trouble putting on socks DIF by age, another item at same location on logit scale

20-items fit the Rasch model Item-Trait interaction Total item chi square >.05: p =.424 Item Fit Item residuals all < ±2.0 Item Chi Square and F-stat all p >.01 No DIF by age and gender PSI = 0.83

Items removed Stratford & Binkley version: 2,15,17,19,20,24 Williams & Myers version: 2,15,19,20,22,24 Rasch 21-item version: 5,9,16,17

24-item RDQ: Targetting Increasing item difficulty Increasing person ability Decreasing item difficulty Decreasing person ability 19 dress with help avoid heavy jobs -2.35

24-item RDQ: Targetting Increasing item difficulty Increasing person ability Decreasing item difficulty Decreasing person ability gap cluster

24-item RDQ 18-item RDQ Stratford 17 Walk short distances 2 Change position frequently 19 Dress with help 24 Stay in bed 15 Appetite not good 20 Sit most of the day

24-item RDQ 18-item RDQ Williams

24-item RDQ 20-item Rasch selection

Raw Scores Vs Rasch Measure Change of 5 points from 10 to 5 = 1.16 logits Change of 5 points from 5 to 0 = 2.58 logits

Conclusions Traditional and Modern Test Theory approaches reject different items Rejecting items of very low/high frequency results in truncated scale RDQ can be made to fit Rasch model, but targetting is poor Gaps in item difficulty locations No items of sufficient difficulty for high ability persons

Rasch Group Meeting Swinburne Hawthorn Monday 5 th Dec, 4.00pm Room AR103 Graduate School of Research (next door to Haddon’s coffee shop in campus centre) Megan Davidson Julie Pallant