Children base trait inferences about people on direct observations of behavior. In some situations, these inferences might conflict with information supplied by others. This study examined 3- to 6-year-olds' willingness to change their own trait attributions about an actor after receiving a consistent or inconsistent trait label from an authority…

"Simulation-based inference" (e.g., bootstrapping and randomization tests) has been advocated recently with the goal of improving student understanding of statistical inference, as well as the statistical investigative process as a whole. Preliminary assessment data have been largely positive. This article describes the analysis of the…

Calls for evidence-based policy often fail to recognise the fundamentally political nature of policy making. Policy makers must identify, evaluate and utilise evidence to solve policy problems in the face of competing priorities and political agendas. Evidence should inform but cannot determine policy choices. This paper draws on theories of…

A large number of approaches have been proposed for estimating and testing the significance of indirect effects in mediation models. In this study, four sets of Monte Carlo simulations involving full latent variable structural equation models were run in order to contrast the effectiveness of the currently popular bias-corrected bootstrapping…

This study is focused on conceptual paper and the purpose of this study is to conduct an empirical investigation into the Malaysian Preschool institutions, focusing on measuring their technical efficiency and productivity changes. This study is to examine the nature of productivity changes by means of bootstrapped Malmquist TFP indices. The study…

This article presents the results of a qualitative research with a group of 15 university students of social sciences on informal inferential reasoning developed in a computer environment on concepts involved in the confidence intervals. The results indicate that students developed a correct reasoning about sampling variability and visualized…

When estimating causal effects, unmeasured confounding and model misspecification are both potential sources of bias. We propose a method to simultaneously address both issues in the form of a semi-parametric sensitivity analysis. In particular, our approach incorporates Bayesian Additive Regression Trees into a two-parameter sensitivity analysis…

Purpose: To investigate the effect of combat-related posttraumatic stress disorder (PTSD) on 4 components underlying text-level reading comprehension. Method: A group of 17 veterans with PTSD and 17 matched control participants took part. An experimental task required participants to read and study 3-sentence paragraphs describing semantic…

The transition from preformal and propaedeutic generalization-actions to a symbolically explicit use of the concept of variable has been a matter of significant attention in mathematics education, for example in the context of generalization processes on a preformal level and regarding the specific nature of algebraic concepts. This contribution…

The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's "cognitive plausibility." We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition…

Three studies were jointly conducted by the Office of Research Administration and Office of Proposal Development at Tufts University to evaluate the services within each respective office. The studies featured assessments that used, respectively, (1) quantitative metrics; (2) a quantitative satisfaction survey with limited qualitative questions;…

Briggs and Peck (2015) have written a thought-provoking article on the use of learning progressions in the design of vertical scales that support inferences about student growth. Organized learning models, including learning trajectories, learning progressions, and learning maps have been the subject of research for many years, but more recently…

This article summarizes a conceptual framework and simple mathematical methods of estimating the probability that one event was a necessary cause of another, as interpreted by lawmakers. We show that the fusion of observational and experimental data can yield informative bounds that, under certain circumstances, meet legal criteria of causation.…

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of…

This article presents a simple approach to making quick sample size estimates for basic hypothesis tests. Although there are many sources available for estimating sample sizes, methods are not often integrated across statistical tests, levels of measurement of variables, or effect sizes. A few parameters are required to estimate sample sizes and…