Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Click here to sign up for SAGE Journal Email Alerts today!

Sign In to gain access to subscriptions and/or personal tools.
Educational and Psychological Measurement
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Smith, R. M.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

The Distributional Properties of Rasch Standardized Residuals

Richard M. Smith

American Dental Association

This study was concerned with an investigation of the distributional properties of the standardized residual that is commonly used in Rasch model calibration programs to develop various indices of item and person fit. There were two aspects of this study: (a) an investigation of the distributional properties of the standardized residuals when the data fit the model and (b) the power of the standardized residual to detect measurement disturbances. This study was based on simulated data to control for the presence of confounding factors, such as multi-dimensionality, differences in the slopes of item characteristic curves, and guessing. The results indicated that when that data fit the model the distributional properties of the standardized residuals were close to hypothesized mean and standard deviation and that it is possible to construct reasonable Type I error rates that can be used as a frame of reference when investigating the fit of actual data to the Rasch model. The analysis of the simulated measurement disturbance data indicated that although the shape of the standardized residual distribution reacts to the presence of the disturbance, the magnitude of the response is small and the residuals lack the power of the item or person fit statistics to detect measurement disturbances.

Educational and Psychological Measurement, Vol. 48, No. 3, 657-667 (1988)
DOI: 10.1177/0013164488483009
Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?


This article has been cited by other articles:


Home page
 Educational and Psychological MeasurementHome page
W.-C. Wang and C.-T. Chen
Item Parameter Recovery, Standard Error Estimates, and Fit Statistics of the Winsteps Program for the Family of Rasch Models
Educational and Psychological Measurement, June 1, 2005; 65(3): 376 - 404.
[Abstract] [PDF]

Home page
 Educational and Psychological MeasurementHome page
I. Styles and D. Andrich
Linking the Standard and Advanced forms of the Raven'S Progressive Matrices in both the Pencil-And-Paper and Computer-Adaptive-Testing Formats
Educational and Psychological Measurement, December 1, 1993; 53(4): 905 - 925.
[Abstract]

Home page
 Educational and Psychological MeasurementHome page
R. M. Smith
The Distributional Properties of Rasch Item Fit Statistics
Educational and Psychological Measurement, September 1, 1991; 51(3): 541 - 565.
[Abstract]