2010.0: Sunday, October 21, 2001: 8:30 AM-4:30 PM |
Oral Session |
| Continuing Education Institute - Developing, Analyzing & Interpreting Outcome Scales with Rasch Measurement |
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| See a complete description of this Institute. |
| Learning Objectives: At the conclusion of the session the participants should be able to:
· What is Measurement
A. Distinguish between ordinal and interval outcome data.
B. Understand the appropriate types of statistical analysis appropriate for the various
levels of measurement.
· Rasch Measurement Models
A. Distinguish between dichotomous, rating scale and partial credit Rasch models.
B. Understand the appropriate methods for converting ordinal observations into
interval measures.
· True Score vs. Rasch Measurement
A. Articulate the methodological shortfalls of the true-score model.
B. Understand the advantages of a philosophy of measurement vs. a theory of data description.
· Estimation Procedures
A. Discuss the various estimation methods available to produce interval measures.
B. Articulate the differences in implementation of estimation procedures in the currently available computer programs.
· Testing the Fit of Data
A. Discuss the importance of the fit of the data to the measurement model from a philosophical and practical perspective.
B. Apply the various test of fit to determine the appropriateness for a data set for this type of analysis.
· Running WINSTEPS
A. Understand the control file and data structure necessary to run WINSTEPS
B. Understand the primary output tables from WINSTEPS.
· Score Reporting /Standard Setting
A. Recognize the importance of the common metric for items and persons to the reporting and program evaluation aspects.
B. Develop an appropriate method for displaying the relationship between ordinal observations and interval measures.
C. Recognize the importance of using objective methods to set standards and the role of the measurement model in the standard setting process.
D. Develop an appropriate method for determining a cut score for discharge or program evaluation.
· Item Bias
A. Discuss the importance of item bias in the measurement of medical outcomes and quality of life.
B. Develop a plan for assessing the impact of differential item functioning on outcome scales.
· Running Facets
A. Understand the control file and data structure necessary to run FACETS.
B. Understand the primary output tables from FACETS.
· Test Equating / Item Banking / Computer Adaptive Testing
A. Recognize need for a common metric for all outcome tools in the same domain.
B. Apply item banking procedures to a pair of instruments designed to measure the same outcome.
C. Identify the role of computer adaptive administration in medical outcomes.
D. Develop a plan for creating a computer adaptive outcome assessment.
· Best Practice Model for Analyzing Poylchotomous Data
A. Articulate the importance of testing the unidimensionality requirement.
B. Develop a systematic plan for assessing the psychometric quality of an instrument.
· Rasch vs. Multi-parameter IRT Models
A. Articulate the importance of the various philosophical approaches to measurement and the impact on the properties of the measures. |
| Sponsor: | APHA-Continuing Education Institutes |
| CE Credits: | CME, Health Education (CHES), Nursing, Pharmacy, Social Work |