Simple web-based IRT score estimation for common metrics: http ...

Simple web-based IRT score estimation for common metrics: http://www.common-metrics.org 1,2

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Felix Fischer , Sandra Nolte , Matthias Rose Department of Psychosomatic Medicine, Center for Internal Medicine and Dermatology 2 Institut for Social Medicine, Epidemiology and Health Economics Charite – Universit¨atsmedizin Berlin, Germany

Background

Common Metrics

Methods

In the field of PRO measurement there is a plethora of measures. For example, it has been estimated that over 100 instruments alone have been designed to measure (aspects) of depression, such as the

Recently, there has been considerable work in establishing instrument independent scales, e.g. for Depression, Anxiety and Physical Functioning. Such models based on Item-Response Theory allow estimation of a common underlying construct, even when different measures have been used.

The application sets up an IRT model with all parameters fixed to the item parameters of the selected common metric. For person parameter estimation we included the Expected A Posteriori (EAP), Bayes Modal (MAP), Weighted Likelihood Estimation (WLE) and Maximum Likelihood (ML) methods. An EAP estimate for Sum Scores is available when your data stem from one measure only. The application was developed using I R (http://cran.r-project.org/) I shiny (http://shiny.rstudio.com/) I mirt (http://cran.r-project.org/package=mirt).

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PHQ-9

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BDI-I and II

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CES-D

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and many more.

This also applies to various other constructs such as Anxiety, Fatigue, Physical Functioning or Quality of Life. But: data obtained through different measures are hard to compare.

Objective We aimed to develop a web application that allows researchers to estimate scores on instrument independent scales more easily. Scales for the measurement of Depression1,2, Anxiety3 and Physical Function4 have been included so far.

1. http://common-metrics.org

2. Select Model

3. Upload Data

4. Check Estimates

5. Assess Precision

6. Download Data

Strengths and Limitations We strongly believe that common metrics offer the chance to set standards in Patient-Reported Outcome Measurement independent of the measures used. The particular strengths of the direct estimation of the latent variable from the response pattern as provided here are: I

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All available information can be used for estimation (e.g. items from several questionnaires). Results have been reported to be slightly more precise compared to the use of cross-walk tables. The precision of each individual score can be assessed. Estimation is also possible in case of missing item responses.

http://www.epidemiologie.charite.de http://www.psychosomatik.charite.de

Nonetheless, there are some limitations of this method: I

Little is known about the validity of these common metrics and they have rarely been validated so far in external samples.

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When comparing scores across different measures, shorter measures might show a tendency towards the scale mean.

In our opinion an enhanced comparability of data - especially data already collected - outweighs these limitations. We encourage you to use our App and share your experiences with us, so that we can further investigate the strengths and limitations for future applicants.

Visit common-metrics.org now!

References 1. Choi et al (2014). Establishing a Common Metric for Depressive Symptoms. Psychological Assessment 2. Wahl et al (2014). Standardization of depression measurement: a common metric was developed for 11 self-report depression measures. Journal of Clinical Epidemiology 3. Schalet et al (2014). Establishing a common metric for self-reported anxiety. Journal of Anxiety Disorders 4. ten Klooster et al (2013). Development and evaluation of a crosswalk between the SF-36 physical functioning scale and Health Assessment Questionnaire disability index in rheumatoid. Health and Quality of Life Outcomes

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