Developing valid and reliable instruments is crucial but costly and time-consuming in health care research and evaluation. The Food and Drug Administration and the National Institutes of Health have set up guidelines for developing patient-reported outcome instruments. However, the guidelines are not applicable to cases of small sample sizes. Instead of using an exact estimation procedure to examine psychometric properties, our Bayesian Instrument Development (BID) method integrates expert data and participant data into a single seamless analysis. Using a novel set of priors, we use simulated data to compare BID to classical instrument development procedures and test the stability of BID. To display BID to non-statisticians, a graphical user interface based on R and WINBUGS is developed and demonstrated with data on a small sample of heart failure patients. Costs were saved by eliminating the need for unnecessary continuation of data collection for larger samples as required by the classical instrument development approach.
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| http://dx.doi.org/10.1177/0146621613517165 | DOI Listing |
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