My EPPP Test Construction

refers to the extent to which a test measures the hypothetical trait (construct) it is intended to measure. Methods for establishing construct validity include correlating test scores with scores on measures that do and do not measure the same trait (convergent and discriminant validity), conducting a factor analysis to assess the test’s factorial validity, determining if changes in test scores reflect expected developmental changes, and seeing if experimental manipulations have the expected impact on test scores.

The extent to which a test adequately samples the domain of information, knowledge, or skill that it purports to measure. Determined primarily by “expert judgment.” Most important for achievement and job sample tests.

Refers to bias introduced into a person’s criterion score as a result of the knowledge of the scorer about his/her performance on the predictor. Tends to artificially inflate the relationship between the predictor and criterion.

Interpretation of a test score in terms of a prespecified standard; i.e., in terms of percent of content correct (percentage score) or of predicted performance on an external criterion (e.g., regression equation, expectancy table).

The type of validity that involves determining the relationship (correlation) between the predictor and the criterion. The correlation coefficient is referred to as the criterion-related validity coefficient. Criterion-related validity can be either concurrent (predictor and criterion scores obtained at about the same time) or predictive (predictor scores obtained before criterion scores).

Process of re-assessing a test’s criterion-related validity on a new sample to check the generalizability of the original validity coefficient. Ordinarily, the validity coefficient “shrinks” (becomes smaller) on cross-validation because the chance factors operating in the original sample are not all present in the cross-validation sample.

A multivariate statistical technique used to determine how many factors (constructs) are needed to account for the intercorrelations among a set of tests, subtests, or test items. Factor analysis can be used to assess a test’s construct validity by indicating the extent to which the test correlates with factors that it would and would not be expected to correlate with. From the perspective of factor analysis, true score variability consists of communality and specificity. Factors identified in a factor analysis can be either orthogonal or oblique.

In a factor matrix, a factor loading is the correlation between a test (or other variable included in the analysis) and a factor and can be squared to determine the amount of variability in the test that is accounted for by the factor. The communality is the total amount of variability in scores on the test that is accounted for by the factor analysis - i.e., by all of the identified factors.

The extent to which a predictor increases decision-making accuracy. Calculated by subtracting the base rate from the positive hit rate. Terms to have linked with incremental validity are predictor and criterion cutoff scores; true and false positives and true and false negatives. True positives are those who scored high on the predictor and criterion; false positives scored high on the predictor but low on the criterion; true negatives scored low on the predictor and the criterion; and false negatives scored low on the predictor but high on the criterion.

When using item response theory, an item characteristic curve (ICC) is constructed for each item by plotting the proportion of examinees in the tryout sample who answered the item correctly against either the total test score, performance on an external criterion, or a mathematically-derived estimate of a latent ability or trait. The curve provides information on the relationship between an examinee’s level on the ability or trait measured by the test and the probability that he/she will respond to the item correctly.

An item’s difficulty level is calculated by dividing the number of individuals who answered the item correctly by the total number of individuals; ranges in value from 0 (very difficult item) to 1.0 (very easy item). In general, an item difficulty index of .50 is preferred because it maximizes differentiation between individuals with high and low ability and helps ensure a high reliability coefficient.

refers to the extent to which a test item discriminates (differentiates) between examinees who obtain high versus low scores on the entire test or on an external criterion. The item discrimination index (D) ranges from -1.0 to +1.0. If all examinees in the upper group and none in the lower group answered the item correctly, D is +1.0; if none of the examinees in the upper group and all examinees in the lower group answered the item correctly, D equals -1.0.

A correlation coefficient used to assess inter-rater reliability.

A systematic way to organize the correlation coefficients obtained when assessing a measure’s convergent and discriminant validity (which, in turn, provides evidence of construct validity). Requires measuring at least two different traits using at least two different methods for each trait. Terms to have linked with multitrait-multimethod matrix are monotrait-monomethod, monotrait-heteromethod, heterotrait-monomethod, and heterotrait-heteromethod coefficients.

Interpretation of an examinee’s test performance relative to the performance of examinees in a normative (standardization) sample. Percentile ranks and standard scores (e.g., z-scores and T scores) are types of norm-referenced scores.

In factor analysis, an orthogonal rotation of the identified factors produces uncorrelated factors, while an oblique rotation produces correlated factors. Rotation is done to simplify the interpretation of the identified factors.

is a necessary but not sufficient condition for validity. In terms of criterion-related validity, the validity coefficient can be no greater than the square root of the product of the reliabilities of the predictor and criterion.

In test construction, this refers to the extent to which test items contribute to achieving the stated goals of testing.

refers to the consistency of test scores; i.e., the extent to which a test measures an attribute without being affected by random fluctuations (measurement error) that produce inconsistencies over time, across items, or over different forms. Methods for establishing reliability include test-retest, alternative forms, split-half, coefficient alpha, and inter-rater. Most produce a reliability coefficient, which is interpreted directly as a measure of true score variability - e.g., a reliability of .80 indicates that 80% of variability in test scores is true score variability.

provide information about a predictor’s accuracy when administered to a group of individuals who are known to have or not have the disorder (or other characteristic) of interest. Sensitivity is the percent of people in the tryout sample who have the disorder and were accurately identified by the predictor as having the disorder. Specificity is the percent of people in the tryout sample who do not have the disorder and were accurately identified by the predictor as not having the disorder.

is a method for assessing internal consistency reliability and involves “splitting” the test in half (e.g., odd- versus even-numbered items) and correlating examinees’ scores on the two halves of the test. The split-half reliability coefficient tends to underestimate a test’s actual reliability and is usually corrected with the Spearman-Brown formula, which estimates what the test’s reliability would be if it were based on the full length of the test.

An index of error when predicting criterion scores from predictor scores. Used to construct a confidence interval around an examinee’s predicted criterion score. Its magnitude depends on two factors: the criterion’s standard deviation and the predictor’s validity coefficient.

An index of measurement error. Used to construct a confidence interval around an examinee’s obtained test score. Its magnitude depends on two factors: the test’s standard deviation and reliability coefficient.

A test’s reliability can be increased in several ways. One way is to increase the test length by adding items of similar content and quality. Another is to increase the heterogeneity of the sample in terms of the attribute(s) measured by the test, which will increase the range of scores.

A method for assessing reliability that involves administering the same test to the same group of examinees on two different occasions and correlating the two sets of scores. Yields a coefficient of stability.