Interactive computer simulations are commonly used as pedagogical tools to support students' statistical reasoning. This paper examines whether and how these simulations enable their intended effects. We begin by contrasting two theoretical frameworks--"dual processes" and "grounded cognition"--in the context of people's…

Several branches of the potential outcome causal inference literature have discussed the merits of blocking versus complete randomization. Some have concluded it can never hurt the precision of estimates, and some have concluded it can hurt. In this article, we reconcile these apparently conflicting views, give a more thorough discussion of what…

Thanks to the latest developments in network-oriented sampling, it is now possible to measure "transnational social fields," or emergent social structures that connect places or regions in different countries. These structures are instrumental in explaining sociocultural phenomena like the emergence of ethnic or demographic enclaves,…

In describing how people generalize from observed samples of data to novel cases, theories of inductive inference have emphasized the learner's reliance on the contents of the sample. More recently, a growing body of literature suggests that different assumptions about how a data sample was generated can lead the learner to draw qualitatively…

The aim of this study is to investigate the impact of different logistic regression estimators applied to RDS studies via simulation and the analysis of empirical data. Four simulated populations were created with different connectivity characteristics. Each simulated individual received two attributes, one of them associated to the infection…

In this report, we analyze students' learning of compound probability by describing connections they generated while engaged with tasks involving two independent events. Several of their connections were compatible with the development of expertise, such as recognizing the need to determine sample spaces across a variety of situations and noting…

One of the most important developments in the current era of social sciences is the growing availability and diversity of data, big and small. Social scientists increasingly combine information from multiple data sets in their research. While conducting statistical analyses with linked data is relatively straightforward, borrowing information…

Background: The generalizability of a study's results continues to be at the forefront of concerns in evaluation research in education (Tipton & Olsen, 2018). Over the past decade, statisticians have developed methods, mainly based on propensity scores, to improve generalizations in the absence of random sampling (Stuart et al., 2011; Tipton,…

Fetters et al.'s (2013) mixed methods integration framework uses construction metaphors: building, connecting, merging, and embedding. In a similar vein, this article uses an architectural metaphor and introduces design patterns as building blocks for mixed methods research design. A design pattern embeds one specific design decision into its…

Purpose: This study describes participant diversity in Williams syndrome (WS) intervention studies. Methods: A literature search was conducted to identify prospective treatment studies including participants with WS. Data was extracted on the reporting of and information provided on age, sex, cognitive ability, socioeconomic status, race, and…

Accurate item parameters and standard errors (SEs) are crucial for many multidimensional item response theory (MIRT) applications. A recent study proposed the Gaussian Variational Expectation Maximization (GVEM) algorithm to improve computational efficiency and estimation accuracy (Cho et al., 2021). However, the SE estimation procedure has yet to…

Latent class analysis (LCA) is a widely used technique for detecting unobserved population heterogeneity in cross-sectional data. Despite its popularity, the performance of LCA is not well understood. In this study, we evaluate the performance of LCA with binary data by examining classification accuracy, parameter estimation accuracy, and coverage…

This paper focuses on the considerations in determining the number of participants for qualitative research because of the lack of clear guidelines in this area. The study has employed a semi-systematic literature review that is embedded with the researcher's experience. The study has concluded that the purpose of the research, methodological…

The quality of mixing methods has been widely debated in the field of applied linguistics (AL) and the integration of data from both quantitative and qualitative research paradigms has always been open to controversy. The present study was aimed at recognizing the status quo of MMR in AL, investigating the nature of various sections of MMR…

Item response theory (IRT) models typically rely on a normality assumption for subject-specific latent traits, which is often unrealistic in practice. Semiparametric extensions based on Dirichlet process mixtures (DPMs) offer a more flexible representation of the unknown distribution of the latent trait. However, the use of such models in the IRT…