Perspectives on Developing and Publishing Clinical Tests David S. Herzberg, PhD.

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Transcript of Perspectives on Developing and Publishing Clinical Tests David S. Herzberg, PhD.

Perspectives on Developing and Publishing Clinical Tests

David S. Herzberg, PhD

A Career Path Less Travelled . . .

• PhD, Clinical Psychology, 1998• Post-Doc in NP, 1998-2000

• Chief Operating Officer• (VP R&D, 2009 – 2014)• (Project Director, 2000-2008)

Topics

• Overview of Test Publishing• Test Construction–Item Scaling–Norms Development

Test Publishers have a Trade Group!

• Certification/Licensure• Education• Industrial/Organizational• Workforce Skills Credentialing• Clinical

Clinical Publishers

Test Publishing Is A Process . . .

• Author: Acquiring IP through publishing contract• Planning: Deliverables, budget, timeline• R&D: Data collection, analysis, technical writing• Editorial: Optimize the text content• Design: Optimize the user interface• Technology: Online administration, scoring• Marketing: Present the work to an audience• Launch: Publish test for clinical use

Topics

• Overview of Test Publishing• Test Construction–Item Scaling–Norms Development

How Difficult Is A Test Item?

WISC-IV Comprehension9. Tell me some reasons that you should turn off lights when no one is using them.

• Sample A: Typically developing 4th graders– 90% ≥ 1-point response

• Sample B: 2nd graders with moderate ADHD– 30% ≥ 1-point response

Rasch Measurement Principles

• Also called IRT, single-parameter models• Assumes unidimensionality of measurement• Single numerical measure for both item

difficulty and person ability– Logit scale: mean = 0, SD = 1– Can be transformed

• “Sample-free” measurement

Rasch Probability Function

Item Characteristic Curve

Item Information Function

SIPT Space Visualization Item Map

Topics

• Overview of Test Publishing• Test Construction–Item Scaling–Norms Development

Normative Reference Samples

Normal Curve and Standard Scores

Are these norms?

Normally Distributed Test Scores

Skewed Distribution Within Narrow Age Band

Skewed Distributions Within Age Bands Lead To Nonsensical Standard Scores

Age Year Raw Score Mean SD

6 45 8

7 47 4

8 49 9

9 51 7

Example: Raw Score = 40• Age 7 years, 11 mo, 29 days: SS = 74• Age 8 years, 0 mo, 1 day: SS = 87 ????

Using Excel To Smooth Means, SDs

Inferential Norming

Questions or Comments?dherzberg@wpspublish.com

www.wpspublish.com