Cultural patterns of evasive answer bias in surveys

Complete and accurate survey data are key input for research, policy, and decision making in many disciplines. However, survey respondents do not always fully cooperate, such that they skip some items or overuse the “don’t know” answer option. Evasive answer bias reflects different information than overall survey response rates, leading to item missing data and causing substantial inaccuracies in survey results. Using data from the World Values Survey, this article identifies the magnitude of the problem, then relies on individual data and country-level cultural values to derive patterns of and reasons for this evasive answer bias. While skipping answers happens less often in collectivistic and low power distance cultures, the choice of the “don’t know” option is not significantly influenced by any cultural dimension. Across countries, the effect of cultural values is stronger for female than for male respondents. Accordingly, cross-cultural researchers are advised to use advanced imputation rather than deletion methods for handling missing data.

New scores for the Category Test: measures of interference for subtests 5 and 6

The Category Test is a well-known neuropsychological instrument used to assess concept formation and higher executive abilities. The present study investigated the utility of additional scores for the Category Test. We used principles developed in cognitive psychology to create several new measures for subtests 5 and 6 of this test. These scores were primarily designed to be sensitive to interference effects of learning decision rules from subtest 2, subtest 3, and subtest 4. The new scores as well as the total error scores from subtests 5 and 6 were used to discriminate subjects with documented brain injury from subjects who were neurologically normal based on neuroimaging and neurologic evaluation. The Category Test was given following Reitan's (1979) instructions, with the exception that no additional prompting was given to participants who struggled early with the test in order to reduce the "executive" guidance of the examiner. Because any "interference" from earlier subtests on performance of subtest 5 and subtest 6 should be related to mastery of these earlier subtests, the normal group was matched to the brain-impaired group on which subtest(s) they learned. This resulted in four learning groups: (a) learned subtests 3 and 4; (b) learned subtest 4 but not 3; (c) learned subtest 3 but not 4; and (d) failed to learn either subtest. ANOVA analyses revealed that the three measures of interference were significantly greater in the brain-damaged group than in the normal controls. Also, specific interference measures were related to specific prior subtest mastery, thus providing support for a proactive interference effect. In addition, we have evidence that our new measures may be selectively sensitive to frontal system dysfunction.

MMPI-2: Confidence intervals for random responding to the F, F Back, and VRIN scales

Several studies have investigated random responding to the F, F Back, and VRIN scales. Only one study attempted to provide practical cutoff scores for these scales, but was unable to reach definitive cutoffs. This study uses the normal approximation to the binomial distribution and provides confidence interval bounds for random responding at the 95, 90, and 85% levels for the F, F Back, and VRIN scales. The possibility that humans asked to respond randomly produce F, F Back, and VRIN scores different from computer-generated random scores was investigated. The results show nonsignificant differences between human and computer responses for the F and F Back scales and mixed results for the VRIN scale.

Millon Clinical Multiaxial Inventory (MCMI-III): the inability of the validity conditions to detect random responders

The effectiveness of the MCMI-III Validity scale, Scale X, and the Clinical Personality Pattern scales to detect random responding is put to the test. The binomial expansion and Monte Carlo techniques were used. If the examiner is willing to interpret tests of questionable validity, then 50% of the random responders will not be detected. Scale X and the Clinical Personality Pattern scales were useless in detecting random responders.