Ant colony optimization for parallel test assembly.

Ant colony optimization (ACO) algorithms have previously been used to compile single short scales of psychological constructs. In the present article, we showcase the versatility of the ACO to construct multiple parallel short scales that adhere to several competing and interacting criteria simultaneously. Based on an initial pool of 120 knowledge items, we assembled three 12-item tests that (a) adequately cover the construct at the domain level, (b) follow a unidimensional measurement model, (c) allow reliable and (d) precise measurement of factual knowledge, and (e) are gender-fair. Moreover, we aligned the test characteristic and test information functions of the three tests to establish the equivalence of the tests. We cross-validated the assembled short scales and investigated their association with the full scale and covariates that were not included in the optimization procedure. Finally, we discuss potential extensions to metaheuristic test assembly and the equivalence of parallel knowledge tests in general.

Longitudinal measurement invariance of neuropsychological tests in a diverse sample from the ELSA-Brasil study

Objective: Longitudinal measurement invariance analyses are an important way to assess a test's ability to estimate the underlying construct over time, ensuring that cognitive scores across visits represent a similar underlying construct, and that changes in test performance are attributable to individual change in cognitive abilities. We aimed to evaluate longitudinal measurement invariance in a large, social and culturally diverse sample over time. Methods: A total of 5,949 participants from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) were included, whose cognition was reassessed after four years. Longitudinal measurement invariance analysis was performed by comparing a nested series of multiple-group confirmatory factor analysis models (for memory and executive function factors). Results: Configural, metric, scalar and strict invariance were tested and supported over time. Conclusion: Cognitive temporal changes in this sample are more likely to be due to normal and/or pathological aging. Testing longitudinal measurement invariance is essential for diverse samples at high risk of dementia, such as in low- and middle-income countries.

The Development of an Instrument for Longitudinal Learning Diagnosis of Rational Number Operations Based on Parallel Tests.

The precondition of the measurement of longitudinal learning is a high-quality instrument for longitudinal learning diagnosis. This study developed an instrument for longitudinal learning diagnosis of rational number operations. In order to provide a reference for practitioners to develop the instrument for longitudinal learning diagnosis, the development process was presented step by step. The development process contains three main phases, the Q-matrix construction and item development, the preliminary/pilot test for item quality monitoring, and the formal test for test quality control. The results of this study indicate that (a) both the overall quality of the tests and the quality of each item are good enough and that (b) the three tests meet the requirements of parallel tests, which can be used as an instrument for longitudinal learning diagnosis to track students' learning.

Parallel Tests Using Culture, Xpert MTB/RIF, and SAT-TB in Sputum Plus Bronchial Alveolar Lavage Fluid Significantly Increase Diagnostic Performance of Smear-Negative Pulmonary Tuberculosis.

At present, tuberculosis remains a serious threat to human health. The diagnosis of pulmonary tuberculosis (PTB) is still difficult, and the prominent challenge for diagnosis is the lack of a highly sensitive and specific method. In order to explore the diagnostic value of parallel tests, this study prospectively enrolled 258 patients with smear-negative PTB from May 2, 2015 to December 31, 2016. The sputum specimens and bronchial alveolar lavage fluid (BALF) samples from all patients were assessed for MTB detection by culture, Xpert MTB/RIF, and simultaneous amplification and testing method for TB (SAT-TB). Overall, the sensitivity of any single test using culture, Xpert MTB/RIF, or SAT-TB was lower than that for parallel tests (p < 0.05), and the sensitivity rates for MTB detection in BALF were significantly higher than those in sputum samples. There were lower agreements in the detection results between sputum samples and BALF for all tests (p < 0.05). The parallel tests models of using culture plus Xpert MTB/RIF plus SAT-TB, culture plus Xpert, or culture plus SAT-TB achieved higher sensitivities compared with all three single test models (p < 0.05). Additionally, joint detection using sputum and BALF samples achieved a high sensitivity (0.8566, 95% CI: 0.8086-0.8941). In conclusion, the parallel tests model using culture, Xpert MTB/RIF, and SAT-TB in sputum plus BALF significantly increases the diagnostic performance of smear-negative PTB; thus, this method should be applied clinically when PTB is suspected but smear results are negative.

Test Reliability at the Individual Level.

Reliability has a long history as one of the key psychometric properties of a test. However, a given test might not measure people equally reliably. Test scores from some individuals may have considerably greater error than others. This study proposed two approaches using intraindividual variation to estimate test reliability for each person. A simulation study suggested that the parallel tests approach and the structural equation modeling approach recovered the simulated reliability coefficients. Then in an empirical study, where forty-five females were measured daily on the Positive and Negative Affect Schedule (PANAS) for 45 consecutive days, separate estimates of reliability were generated for each person. Results showed that reliability estimates of the PANAS varied substantially from person to person. The methods provided in this article apply to tests measuring changeable attributes and require repeated measures across time on each individual. This article also provides a set of parallel forms of PANAS.

The Importance of the Assumption of Uncorrelated Errors in Psychometric Theory.

A critical discussion of the assumption of uncorrelated errors in classical psychometric theory and its applications is provided. It is pointed out that this assumption is essential for a number of fundamental results and underlies the concept of parallel tests, the Spearman-Brown's prophecy and the correction for attenuation formulas as well as the discrepancy between observed and true correlations, and the upper bound property of the reliability index with respect to validity. These relationships are shown not to hold if the errors of considered pairs of tests are correlated. The assumption of lack of error correlation is demonstrated not to be testable using standard covariance structure analysis for pairs of indivisible measures evaluating the same true score with identical error variances.