1 / 14

Measuring Change Retrospectively: An Examination Based on Item Response Theory

Measuring Change Retrospectively: An Examination Based on Item Response Theory. S. Bartholomew Craig Kaplan DeVries, Inc. Charles J. Palus & Sharon Rogolsky Center for Creative Leadership. How to obtain this paper. Download it from the Internet at http://sbcraig.com

Download Presentation

Measuring Change Retrospectively: An Examination Based on Item Response Theory

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Measuring Change Retrospectively:An Examination Based onItem Response Theory S. Bartholomew CraigKaplan DeVries, Inc. Charles J. Palus & Sharon RogolskyCenter for Creative Leadership

  2. How to obtain this paper • Download it from the Internet athttp://sbcraig.com • Request an electronic copy by sending email to bcraig@kaplandevries.com • The old fashioned way…Pick up a paper copy from the front of the room

  3. Overview • Retrospective measurement as a solution to the problem of beta change (response shift bias) • Beta change as differential item / test functioning (DIF / DTF) • Comparison of retrospective measurement and IRT-based DIF methods for detecting beta change

  4. What is Beta Change? • Golembiewski, Billingsley, & Yeager (1976) • “response shift bias” (Howard & Dailey, 1979) • “instrumentation bias” (Campbell & Stanley, 1963) • Occurs when the intervention being evaluated alters raters’ mental frame of reference • Renders pre- and post-intervention scores incomparable • Post-intervention metric usually more severe

  5. Item Response Theoryand Beta Change • IRT models the probability of item responses as a function of item characteristics and the latent trait being measured (θ). • When probabilities of responses are different for different groups, differential item functioning (DIF) is said to occur. • By treating pre- and post-intervention raters as separate groups, IRT can identify beta change as DIF.

  6. Item Response TheoryItem Parameters • As a set, an item’s parameters define its relation to the latent trait (θ). • Discrimination parameter (a) • one per item • higher values mean better discrimination among individuals • Difficulty parameters (b) • each item has one for each response category • indicates point on θ where 50% choose that category

  7. Differential Functioning ofItems and Tests (DFIT) • Raju, Van der Linden, & Fleer (1995) • Models DIF as difference in expected item response for raters with identical perceptions of ratee performance • Allows for item- and scale-level analyses • NCDIF • DTF • CDIF

  8. “Carefully weighs consequences of contemplated action”

  9. “Competent at dealing with people’s feelings”

  10. Participants and Measure • 415 raters from US and New Zealand • 29 focal program participants were rated • raters were superiors, peers, and subordinates • analyses used sample sizes from 20 to 278 • 54 items from the SkillChange 360° assessment instrument were analyzed • “now” and “about one year ago” ratings at Times 1 & 2 • 9-point response format (collapsed to 4) • unidimensional • Cronbach’s alpha = .97

  11. Analyses • Beta change assessed as in past research • repeated measures ANOVA using observed scores (N = ~20) • examine for significant pre-then differences • Beta change assessed using IRT / DFIT • compare pre-then, pre-post, and post-then • Ns = 278, 78, 59 • Assessed convergence of the two methods

  12. Results

  13. Conclusions • IRT-based DIF methods have promise for detecting beta change • Most items do not exhibit beta change, regardless of detection method used • Pre-Then differences are not a reliable indicator of beta change (FPs & FNs) • Post-Then differences are generally on the same metric, but what they reflect is uncertain

  14. Limitations • Small sample size (especially post-program) • Rater groups collapsed(insufficient N to examine self ratings alone) • Response categories collapsed (results may not generalize to uncollapsed 9-pt. scale) • Experiment-wise Type I error rate > .05

More Related