This study evaluated whether the addition of a writing section to the SAT Reasoning Test™ (referred to as the SAT® in this study) would impact test‐taker performance because of fatigue caused by increased test length. The study also investigated test‐takers' subjective feelings of fatigue. Ninety‐seven test‐takers were randomly assigned to three groups: the first group took a current SAT with no essay; the second group took a pseudo new SAT composed of the current SAT plus an essay, with the essay appearing in the first section of the test; and the third group also took the pseudo new SAT with an essay, but with the essay in the last section. Test‐taker performance on the verbal and math sections and the essay was then evaluated and compared. The results indicated that while the extended testing time for the new SAT may cause test‐takers to feel fatigued, fatigue did not affect test‐taker performance.
Issues of equity and fairness across subgroups of the population (e.g., gender or ethnicity) must be seriously considered in any standardized testing program. For this reason, many testing programs require some means for assessing test characteristics, such as reliability, for subgroups of the population. However, often only small sample sizes are available for the subgroups of interest. Traditionally used reliability estimates (e.g., Cronbach's alpha) can have low precision for small samples. This study investigated whether an empirical Bayes (EB) technique could produce more precise reliability estimates than traditional methods in the presence of small samples. Several Bayesian estimates were compared to estimates obtained by other methods (e.g., the traditionally and currently used Cronbach's alpha coefficient), in terms of both bias and variance. A secondary purpose of this study was to compare the various EB approaches across different sample sizes. This paper also discusses EB estimates of standard error of measurement (SEM), their accuracy and precision, and how they compare with SEM estimates derived from the alpha.
This study evaluated the criterion-related validity for the Speed of Processing (SP) factor of the Differential Ability Scales (DAS; Elliott, 1990). The SP factor is comprised of one subtest score (Speed of Information Processing) based on results from factor analyses. Participants were an epidemiological sample (N= 1,400) stratified, within age levels, in proportion to census data on demography (e.g., race, gender, parents' educational levels). From this cohort, groups with unusual SP strengths and SP weaknesses were identified using General Cognitive Ability (GCA) scores from the DAS as contrasts (i.e., SP>GCA and GCA>SP differences at a population prevalence < 5%). The SP>GCA group (n= 60) and the GCASP group (n = 60) were matched to respective controls (where each control n = 60) on the demographic variables listed above and GCAs. Each group and its control were compared across three norm-referenced measures of achievement and six teacher-rated indices of behavioral adjustment. Comparisons failed to show significant differences on any criterion variable. Results are discussed in the context of how well epidemiological samples evaluate the validity of ability profiles and the need for future research to use more representative measures of processing speed (i.e., those with two or more subtests contributing to the factor).
Pseudo Bayes probability estimates are weighted averages of raw and modeled probabilities; these estimates have been studied primarily in nonpsychometric contexts. The purpose of this study was to evaluate pseudo Bayes probability estimates as applied to the estimation of psychometric test score distributions and chained equipercentile equating functions. Population test score distributions were created from actual test data and random samples of varied size were drawn from the populations. Pseudo Bayes estimation was applied to the random samples, using ranges of loglinear models and weights in the pseudo Bayes estimates' weighted averages of the raw and modeled test score probabilities. Equipercentile equating functions based on the pseudo Bayes estimates were also evaluated. Results indicated that the pseudo Bayes estimates have the potential to improve estimation accuracy for test score distributions and chained equipercentile equating functions in situations where loglinear modeling is not ideal and where finding the population loglinear model selection is not likely.
This study examined whether ability scores from the Wechsler Intelligence Scale for Children-Third Edition (WISC-III) showed criterion-related bias. Participants (N= 832) comprised a referral cohort between ages 8 and 16 years that differed by race (Anglo, African American) and gender. Verbal, Performance, and Full Scale IQs from the WISC-III were used to predict Reading, Mathematics, Language, and Writing Composites from the Wechsler Individual Achievement Test (WIAT). Unlike previous research with the WISCIII, 50% of the analyses (12 out of 24) showed statistically significant effects. However, in all instances where bias was found, differences in regressions were statistically significant for intercepts, but not for slopes, and served to overpredict the performance of minority groups (African Americans, females) relative to majority groups (Anglos, males). Results are discussed in the context of how instances of differences in intercepts could mislead psychologists in interpreting children's ability scores.
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