Quantile lower bounds to reliability based on locally optimal splits.

Extending the theory of lower bounds to reliability based on splits given by Guttman (in Psychometrika 53, 63-70, 1945), this paper introduces quantile lower bound coefficients λ 4(Q) that refer to cumulative proportions of potential locally optimal "split-half" coefficients that are below a particular point Q in the distribution of split-halves based on different partitions of variables into two sets. Interesting quantile values are Q=0.05,0.50,0.95,1.00 with λ 4(0.05)≤λ 4(0.50)≤λ 4(0.95)≤λ 4(1.0). Only the global optimum λ 4(1.0), Guttman's maximal λ 4, has previously been considered to be interesting, but in small samples it substantially overestimates population reliability ρ. The three coefficients λ 4(0.05), λ 4(0.50), and λ 4(0.95) provide new lower bounds to reliability. The smallest, λ 4(0.05), provides the most protection against capitalizing on chance associations, and thus overestimation, λ 4(0.50) is the median of these coefficients, while λ 4(0.95) tends to overestimate reliability, but also exhibits less bias than previous estimators. Computational theory, algorithm, and publicly available code based in R are provided to compute these coefficients. Simulation studies evaluate the performance of these coefficients and compare them to coefficient alpha and the greatest lower bound under several population reliability structures.

Brief report: independent validation of autism spectrum disorder case status in the Utah Autism and Developmental Disabilities Monitoring (ADDM) Network Site.

An independent validation was conducted of the Utah Autism and Developmental Disabilities Monitoring Network's (UT-ADDM) classification of children with autism spectrum disorder (ASD). UT-ADDM final case status (n = 90) was compared with final case status as determined by independent external expert reviewers (EERs). Inter-rater reliability (ICC = 0.84), specificity [0.83 (95 % CI 0.74-0.90)], and sensitivity [0.99 (95 % CI 0.96-1.00)] were high for ASD case versus non-case classification between UT-ADDM and EER. At least one EER disagreed with UT-ADDM on ASD final case status on nine out of 30 records; however, all three EERs disagreed with UT-ADDM for only one record. Findings based on limited data suggest that children with ASD as identified by UT-ADDM are consistently classified as ASD cases by independent autism experts.