Twenty nine students who had previously taken an undergraduate thermal physics course were interviewed about their basic knowledge about statistical mechanics at the undergraduate level. Of these 29, fourteen were undergraduate students, and fifteen were graduate students at varying stages of their career. This project aimed to identify and…

With the prevalence of missing data in social science research, it is necessary to use methods for handling missing data. One framework in which data with missing values can still be used for parameter estimation is the Bayesian framework. In this tutorial, different missing data mechanisms including Missing Completely at Random, Missing at…

Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…

In this article, we present a two-stage estimation approach applied to multilevel latent class analysis (LCA) with covariates. We separate the estimation of the measurement and structural model. This makes the extension of the structural model computationally efficient. We investigate the robustness against misspecifications of the proposed…

Despite the broad appeal of missing data handling approaches that assume a missing at random (MAR) mechanism (e.g., multiple imputation and maximum likelihood estimation), some very common analysis models in the behavioral science literature are known to cause bias-inducing problems for these approaches. Regression models with incomplete…

This paper presents partial results of a one-year project funded by a grant from Mexico's National Science and Technology Council and the National Institute for the Evaluation of Education that was designed to characterize the teaching of statistics in Mexican high school education. Work was organized in two 6-month phases. The first stage…

How do we deal with unlikely witness testimonies? Whether in legal or everyday reasoning, corroborative evidence is generally considered a strong marker of support for the reported hypothesis. However, questions remain regarding how the prior probability, or base rate, of that hypothesis interacts with corroboration. Using a Bayesian network…

Statistical methods are increasingly being used to integrate findings from the ever-expanding universe of empirical research. Meta-analysis encompasses various techniques for synthesizing summary statistics, and mega-analysis pools raw data across studies. This paper offers an introduction to meta-analysis and mega-analysis that complements the…

Oftentimes in many fields of the social and natural sciences, data are obtained within a nested structure (e.g., students within schools). To effectively analyze data with such a structure, multilevel models are frequently employed. The present study utilizes a Monte Carlo simulation to compare several novel multilevel classification algorithms…

An a-posteriori multicentre reliability study was conducted to compare the reliability and magnitude of the maximum power (P[subscript max]) and optimal velocity (V[subscript opt]) between the force-power-velocity relationships during the leg cycle-ergometer and bench press throw exercises. The force-power-velocity relationships were determined 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…

While a dot plot depicts data on a quantitative variable without distortion, a boxplot shows only the five-number summary. For large data, to aid in counting, we propose an IVY plot as a companion to a dot plot. Also, for large data, if the variable is approximately normally distributed, as a companion to a boxplot, we propose a Gaussian interval…

Methods for group comparisons using predicted probabilities and marginal effects on probabilities are developed for regression models for binary outcomes. Unlike approaches based on the comparison of regression coefficients across groups, the methods we propose are unaffected by the scalar identification of the coefficients and are expressed in…

Knowledge about the interior density distribution of a planetary body can constrain geophysical processes and reveal information about the origin and evolution of the body. Properties of this interior distribution can be inferred by analyzing gravity acceleration data sampled by orbiting satellites. Usually, the gravity data is complemented with…

One important issue in Bayesian estimation is the determination of an effective informative prior. In hierarchical Bayes models, the uncertainty of hyperparameters in a prior can be further modeled via their own priors, namely, hyper priors. This study introduces a framework to construct hyper priors for both the mean and the variance…