ANALYZING AND ADJUSTING FOR VARIABLES IN A LARGE-SCALE STANDARDIZED-PATIENT EXAMINATION

Background. Structuring a clinical performance examination that uses s tandardized patients (SPs) for large groups of examinees often involve s the use of two or more parallel forms of the examination with differ ent SPs portraying the same case on the different forms. In addition, each form may be administered more than once on different days and/or in different locations. Method. To determine the effects of critical v ariables, such as day of examination, time of day (AM/PM), which of tw o simultaneous forms were taken, and sequencing effects, a univariate nested factorial analysis of variance was conducted for each of four a nnual SP examinations (1990-1993) at the University of Texas Southwest ern Medical School. The examinations were given to approximately 200 s econd-year students per year at the end of their Introduction to Clini cal Medicine course, and were graded on a pass/fail basis. Results. St atistically significant differences were found for the following varia bles: (1) time of day (AM or PM) and day were significant but were inc onsistent and of small magnitude; (2) sequencing for the first two sta tions was significant in each form of the examination and in all four years; and (3) form-within-case differences (i.e., differences between SPs) were significant between the two forms of the examination in eac h year of administration. To minimize the impacts of these variables, two mean equating formulas were applied to the scores. Few examinees' pass/fail status would have been affected by either adjustment. Conclu sion. The parallel-forms examination format is minimally affected by t he variables evaluated and is a fair pass/fail assessment of a student 's performance. Mean equating is a valuable tool in minimizing the pos sibly unfair impact of variables on pass/fail decisions for homogeneou s student populations.