![]() ![]() The scale’s reliability and DC were simultaneously calculated for each simulative dataset. DC refers to the binary classification (1 as one factor and 0 as many factors) used for examining accuracy with the indicators sensitivity, specificity, and area under receiver operating characteristic curve (AUC). Three methods (i.e., dimension interrelation ≥0.7, Horn’s parallel analysis (PA) 95% confidence interval, and individual random eigenvalues) were used for determining one factor to retain. Each item containing 5-point polytomous responses was uniformly distributed in difficulty across a ± 2 logit range. The datasets consisted of (i) five dual correlation coefficients (correl. = 0.3, 0.5, 0.7, 0.9, and 1.0) on two latent traits (i.e., true scores) following a normal distribution and responses to their respective 1/3 and 2/3 items in length (ii) 20 scenarios of item lengths from 5 to 100 and (iii) 20 sample sizes from 50 to 1000. Microsoft Excel Visual Basic for Applications was used to design a computer module for simulating 2000 datasets fitting the Rasch rating scale model. ![]()
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