Matching-adjusted indirect comparison (MAIC) enables indirect comparisons of interventions across separate studies when individual patient-level data (IPD) are available for only one study. Due to its similarity with propensity score weighting, it has been speculated that MAIC can be combined with outcome regression models in the spirit of…

This study evaluates various scoring methods including number-correct scoring, IRT theta scoring, and hybrid scoring in terms of scale-score stability over time. A simulation study was conducted to examine the relative performance of five scoring methods in terms of preserving the first two moments of scale scores for a population in a chain of…

Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial differences in effect modifiers and limited patient-level data. MAIC is based on propensity score weighting, which is sensitive to poor covariate overlap and cannot extrapolate…

Purpose: Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in…

Past research indicates that individuals respond adaptively to contextual factors in multiattribute choice tasks. Yet it remains unclear how this adaptation is cognitively governed. In this article, empirically testable implementations of two prominent competing theoretical frameworks are developed and compared across two multiattribute choice…

Examining the sequential patterns of self-regulated learning (SRL) behaviors is gaining popularity to understand students' performance differences. However, few studies have looked at the transition probabilities among different SRL behaviors. Moreover, there is a lack of research investigating the temporal structures of students' SRL behaviors…

This paper compares the use of confidence intervals (CIs) and a sensitivity analysis called the number needed to disturb (NNTD), in the analysis of research findings expressed as 'effect' sizes. Using 1,000 simulations of randomised trials with up to 1,000 cases in each, the paper shows that both approaches are very similar in outcomes, and each…

This study shows that residual variation can cause problems related to scaling in exponential random graph models (ERGM). Residual variation is likely to exist when there are unmeasured variables in a model--even those uncorrelated with other predictors--or when the logistic form of the model is inappropriate. As a consequence, coefficients cannot…

Meta-analyses often include only a small number of studies ([less than or equal to]5). Estimating between-study heterogeneity is difficult in this situation. An inaccurate estimation of heterogeneity can result in biased effect estimates and too narrow confidence intervals. The beta-binominal model has shown good statistical properties for…

Meta-analyses are often used to synthesize the findings of studies examining the correlational relationship between two continuous variables. When only dichotomous measurements are available for one of the two variables, the biserial correlation coefficient can be used to estimate the product-moment correlation between the two underlying…

Categorical perception (CP) effects manifest as faster or more accurate discrimination between objects that come from different categories compared with objects that come from the same category, controlling for the physical differences between the objects. The most popular explanations of CP effects have relied on perceptual warping causing…

Metrics including Cohen's kappa, precision, recall, and F[subscript 1] are common measures of performance for models of discrete student states, such as a student's affect or behaviour. This study examined discrete model metrics for previously published student model examples to identify situations where metrics provided differing perspectives on…

In item response theory (IRT) modeling, the Fisher information matrix is used for numerous inferential procedures such as estimating parameter standard errors, constructing test statistics, and facilitating test scoring. In principal, these procedures may be carried out using either the expected information or the observed information. However, in…

The use of individual patient data (IPD) in network meta-analysis (NMA) is becoming increasingly popular. However, as most studies do not report IPD, most NMAs are performed using aggregate data for at least some, if not all, of the studies. We investigate the benefits of including varying proportions of IPD studies in an NMA. Several models have…

What are the cognitive mechanisms underlying subjective valuations formed on the basis of sequential experiences of an option's possible outcomes? Ashby and Rakow (2014) have proposed a sliding window model (SWIM), according to which people's valuations represent the average of a limited sample of recent experiences (the size of which is estimated…