Methods for indirect comparisons and network meta-analysis use aggregate level data from multiple studies. A very common, and closely related, scenario is where a company has individual patient data (IPD) from its own trial, but only has published aggregate data from a competitor's trial, and an indirect comparison of the treatments evaluated in…

This paper presents a dynamic Excel visual. The visual has three graphs that are all driven by the same data, so students can see how changes (via Slider controls) in data appear on a univariate graph, a bivariate graph, and a graph that shows a ratio of two variables on one axis. The visual has macros that let a statistics teacher reveal parts of…

Simulation studies involving mixture models inevitably aggregate parameter estimates and other output across numerous replications. A primary issue that arises in these methodological investigations is label switching. The current study compares several label switching corrections that are commonly used when dealing with mixture models. A growth…

In the present study, factor mixture models (FMMs) were used to examine the latent structure underlying the Autism-Spectrum Quotient (AQ) among a sample of 633 undergraduate students. FMM represents a combination of latent-class, person-centered approaches and common-factor, variable-centered approaches to modeling population heterogeneity.…

The importance of the critical interpretive synthesis (CIS) to review quantitative and qualitative research, and to critically develop new theory, is increasingly recognized and evidenced by the increase in published CIS reviews. However, the flexibility embedded in the method hampers its implementation and exacerbates concerns about…

A reference interval provides a basis for physicians to determine whether a measurement is typical of a healthy individual. It can be interpreted as a prediction interval for a new individual from the overall population. However, a reference interval based on a single study may not be representative of the broader population. Meta-analysis can…

A widely applicable procedure of examining proximity to unidimensionality for multicomponent measuring instruments with multidimensional structure is discussed. The method is developed within the framework of latent variable modeling and allows one to point and interval estimate an explained variance proportion-based index that may be considered a…

A two-level data set can be structured in either long format (LF) or wide format (WF), and both have corresponding SEM approaches for estimating multilevel models. Intuitively, one might expect these approaches to perform similarly. However, the two data formats yield data matrices with different numbers of columns and rows, and their "cols :…

For randomized trials that use text as an outcome, traditional approaches for assessing treatment impact require that each document first be manually coded for constructs of interest by trained human raters. This process, the current standard, is both time-consuming and limiting: even the largest human coding efforts are typically constrained to…

Linguistic phenomena (e.g., words and syntactic structure) co-occur with a wide variety of meanings. These systematic correlations can help readers to interpret a text and create predictions about upcoming material. However, to what extent these correlations influence discourse processing is still unknown. We address this question by examining…

The 0.05 boundary within Null Hypothesis Statistical Testing (NHST) "has made a lot of people very angry and been widely regarded as a bad move" (to quote Douglas Adams). Here, we move past meta-scientific arguments and ask an empirical question: What is the psychological standing of the 0.05 boundary for statistical significance? We…

Random encouragement designs are randomized controlled trials (RCTs) that test interventions aimed at increasing participation in a program or activity whose take up is not universal. In these RCTs, instead of randomizing individuals or clusters directly into treatment and control groups to participate in a program or activity, the randomization…

When analyzing treatment effects on test scores, researchers face many choices and competing guidance for scoring tests and modeling results. This study examines the impact of scoring choices through simulation and an empirical application. Results show that estimates from multiple methods applied to the same data will vary because two-step models…

Structural equation models offer a valuable tool for delineating the complicated interrelationships among multiple variables, including observed and latent variables. Over the last few decades, structural equation models have successfully analyzed complete and right-censored survival data, exemplified by wide applications in psychological, social,…

This study draws on quantitative reasoning research to explain how secondary mathematics preservice teachers' (PSTs) modelling competencies changed as they participated in a teacher education programme that integrated modelling experience. Adopting a mixed methods approach, we documented 110 PSTs' competencies in Vietnam using an adapted Modelling…