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Carlos Cinelli; Andrew Forney; Judea Pearl – Sociological Methods & Research, 2024
Many students of statistics and econometrics express frustration with the way a problem known as "bad control" is treated in the traditional literature. The issue arises when the addition of a variable to a regression equation produces an unintended discrepancy between the regression coefficient and the effect that the coefficient is…
Descriptors: Regression (Statistics), Robustness (Statistics), Error of Measurement, Testing Problems
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Aarnes Gudmestad; Thomas A. Metzger – Language Learning, 2025
In this Methods Showcase Article, we illustrate mixed-effects modeling with a multinomial dependent variable as a means of explaining complexities in language. We model data on future-time reference in second language Spanish, which consists of a nominal dependent variable that has three levels, measured over 73 participants. We offer step-by-step…
Descriptors: Second Language Learning, Spanish, Applied Linguistics, Predictor Variables
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Fernando Rios-Avila; Michelle Lee Maroto – Sociological Methods & Research, 2024
Quantile regression (QR) provides an alternative to linear regression (LR) that allows for the estimation of relationships across the distribution of an outcome. However, as highlighted in recent research on the motherhood penalty across the wage distribution, different procedures for conditional and unconditional quantile regression (CQR, UQR)…
Descriptors: Regression (Statistics), Research Methodology, Alternative Assessment, Models
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Youmi Suk – Asia Pacific Education Review, 2024
Regression discontinuity (RD) designs have gained significant popularity as a quasi-experimental device for evaluating education programs and policies. In this paper, we present a comprehensive review of RD designs, focusing on the continuity-based framework, the most widely adopted RD framework. We first review the fundamental aspects of RD…
Descriptors: Educational Research, Preschool Education, Regression (Statistics), Test Validity
Luke W. Miratrix – Grantee Submission, 2022
We are sometimes forced to use the Interrupted Time Series (ITS) design as an identification strategy for potential policy change, such as when we only have a single treated unit and cannot obtain comparable controls. For example, with recent county- and state-wide criminal justice reform efforts, where judicial bodies have changed bail setting…
Descriptors: Causal Models, Case Studies, Quasiexperimental Design, Monte Carlo Methods
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Marek Arendarczyk; Tomasz J. Kozubowski; Anna K. Panorska – Journal of Statistics and Data Science Education, 2023
We provide tools for identification and exploration of data with very large variability having power law tails. Such data describe extreme features of processes such as fire losses, flood, drought, financial gain/loss, hurricanes, population of cities, among others. Prediction and quantification of extreme events are at the forefront of the…
Descriptors: Natural Disasters, Probability, Regression (Statistics), Statistical Analysis
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Wodtke, Geoffrey T. – Sociological Methods & Research, 2020
Social scientists are often interested in estimating the marginal effects of a time-varying treatment on an end-of-study continuous outcome. With observational data, estimating these effects is complicated by the presence of time-varying confounders affected by prior treatments, which may lead to bias in conventional regression and matching…
Descriptors: Regression (Statistics), Computation, Statistical Analysis, Statistical Bias
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Fávero, Luiz Paulo; Souza, Rafael de Freitas; Belfiore, Patrícia; Corrêa, Hamilton Luiz; Haddad, Michel F. C. – Practical Assessment, Research & Evaluation, 2021
In this paper is proposed a straightforward model selection approach that indicates the most suitable count regression model based on relevant data characteristics. The proposed selection approach includes four of the most popular count regression models (i.e. Poisson, negative binomial, and respective zero-inflated frameworks). Moreover, it…
Descriptors: Regression (Statistics), Selection, Statistical Analysis, Models
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Pang, Bo; Nijkamp, Erik; Wu, Ying Nian – Journal of Educational and Behavioral Statistics, 2020
This review covers the core concepts and design decisions of TensorFlow. TensorFlow, originally created by researchers at Google, is the most popular one among the plethora of deep learning libraries. In the field of deep learning, neural networks have achieved tremendous success and gained wide popularity in various areas. This family of models…
Descriptors: Artificial Intelligence, Regression (Statistics), Models, Classification
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Daniel Kasper; Katrin Schulz-Heidorf; Knut Schwippert – Sociological Methods & Research, 2024
In this article, we extend Liao's test for across-group comparisons of the fixed effects from the generalized linear model to the fixed and random effects of the generalized linear mixed model (GLMM). Using as our basis the Wald statistic, we developed an asymptotic test statistic for across-group comparisons of these effects. The test can be…
Descriptors: Models, Achievement Tests, Foreign Countries, International Assessment
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Reinstein, Ilan; Hill, Jennifer; Cook, David A.; Lineberry, Matthew; Pusic, Martin V. – Advances in Health Sciences Education, 2021
Visual diagnosis of radiographs, histology and electrocardiograms lends itself to deliberate practice, facilitated by large online banks of cases. Which cases to supply to which learners in which order is still to be worked out, with there being considerable potential for adapting the learning. Advances in statistical modeling, based on an…
Descriptors: Clinical Diagnosis, Visual Aids, Difficulty Level, Regression (Statistics)
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Davis, Richard A. – Chemical Engineering Education, 2020
A case study of regression analysis based on modeling Gilliland's correlation was described for use in a computational methods course. The case study uses a familiar example to train students in nonlinear least squares regression and to use standardized residual plots for model assessment. Previously published equations for Gilliland's correlation…
Descriptors: Case Studies, Regression (Statistics), Correlation, Least Squares Statistics
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McCarthy, Chris; Lan, Jie; Li, Jieying – PRIMUS, 2019
We present noncompetitive adsorption as "particles in a box with one sticky wall." We start with a general model that can be modeled as a simple ordinary differential equation (ODE). To verify the ODE students run a computer simulation. The ODE's solution imperfectly fits the simulation's data. This leads to the diffusion partial…
Descriptors: Equations (Mathematics), Mathematical Models, Problem Solving, Computer Simulation
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Chance, Beth; Reynolds, Shea – Journal of Statistics Education, 2019
Through a series of explorations, this article will demonstrate how the Kentucky Derby winning times dataset provides various opportunities for introductory and advanced topics, from data processing to model building. Although the final goal may be a prediction interval, the dataset is rich enough for it to appear in several places in an…
Descriptors: Prediction, Statistics, Data Processing, Homework
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York, Richard – International Journal of Social Research Methodology, 2018
A common motivation for adding control variables to statistical models is to reduce the potential for spurious findings when analyzing non-experimental data and to thereby allow for more reliable causal inferences. However, as I show here, unless "all" potential confounding factors are included in an analysis (which is unlikely to be…
Descriptors: Inferences, Control Groups, Correlation, Experimental Groups
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