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Deke, John; Finucane, Mariel; Thal, Daniel – National Center for Education Evaluation and Regional Assistance, 2022
BASIE is a framework for interpreting impact estimates from evaluations. It is an alternative to null hypothesis significance testing. This guide walks researchers through the key steps of applying BASIE, including selecting prior evidence, reporting impact estimates, interpreting impact estimates, and conducting sensitivity analyses. The guide…
Descriptors: Bayesian Statistics, Educational Research, Data Interpretation, Hypothesis Testing
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Danri H. Delport – Numeracy, 2022
A strong foundation in early number concepts is crucial for students' future success in statistics. Despite its importance in statistics, many first-year students struggle to comprehend the normal distribution due to a lack of basic number sense. Students get confused about the order and magnitude of negative z-scores on a standard normal curve or…
Descriptors: Foreign Countries, College Students, Statistics Education, Number Concepts
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Liang, Xinya; Kamata, Akihito; Li, Ji – Educational and Psychological Measurement, 2020
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…
Descriptors: Bayesian Statistics, Randomized Controlled Trials, Effect Size, Sampling
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Cope, Shannon; Chan, Keith; Jansen, Jeroen P. – Research Synthesis Methods, 2020
Background: Network meta-analysis (NMA) of survival data with a multidimensional treatment effect has been introduced as an alternative to NMA based on the proportional hazards assumption. However, these flexible models have some limitations, such as the use of an approximate likelihood based on discrete hazards, rather than a likelihood for…
Descriptors: Multivariate Analysis, Meta Analysis, Network Analysis, Models
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Giada Spaccapanico Proietti; Mariagiulia Matteucci; Stefania Mignani; Bernard P. Veldkamp – Journal of Educational and Behavioral Statistics, 2024
Classical automated test assembly (ATA) methods assume fixed and known coefficients for the constraints and the objective function. This hypothesis is not true for the estimates of item response theory parameters, which are crucial elements in test assembly classical models. To account for uncertainty in ATA, we propose a chance-constrained…
Descriptors: Automation, Computer Assisted Testing, Ambiguity (Context), Item Response Theory
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Serra, Ramiro; Martinez, Cecilia; Vertegaal, Cornelis J. C.; Sundaramoorthy, Prem; Bentum, Mark J. – IEEE Transactions on Education, 2023
Contribution: This article describes how a peer learning strategy called student-led tutorials (SLTs) can improve student performance in an electromagnetism course (EM). This study provides empirical evidence on how promoting student active participation in collaborative problem-solving activities improves performance rates. Background: In 2019,…
Descriptors: College Students, Difficulty Level, Advanced Courses, Tutorial Programs
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Makar, Katie; Allmond, Sue – ZDM: The International Journal on Mathematics Education, 2018
Children have limited exposure to statistical concepts and processes, yet researchers have highlighted multiple benefits of experiences in which they design and/or engage informally with statistical modelling. A study was conducted with a classroom in which students developed and utilised data-based models to respond to the inquiry question,…
Descriptors: Statistics, Mathematical Models, Prediction, Statistical Distributions
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Köse, Alper; Dogan, C. Deha – International Journal of Evaluation and Research in Education, 2019
The aim of this study was to examine the precision of item parameter estimation in different sample sizes and test lengths under three parameter logistic model (3PL) item response theory (IRT) model, where the trait measured by a test was not normally distributed or had a skewed distribution. In the study, number of categories (1-0), and item…
Descriptors: Statistical Bias, Item Response Theory, Simulation, Accuracy
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Son, Sookyoung; Lee, Hyunjung; Jang, Yoona; Yang, Junyeong; Hong, Sehee – Educational and Psychological Measurement, 2019
The purpose of the present study is to compare nonnormal distributions (i.e., t, skew-normal, skew-t with equal skew and skew-t with unequal skew) in growth mixture models (GMMs) based on diverse conditions of a number of time points, sample sizes, and skewness for intercepts. To carry out this research, two simulation studies were conducted with…
Descriptors: Statistical Distributions, Statistical Analysis, Structural Equation Models, Comparative Analysis
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Sánchez Sánchez, Ernesto; García Rios, Víctor N.; Silvestre Castro, Eleazar; Licea, Guadalupe Carrasco – North American Chapter of the International Group for the Psychology of Mathematics Education, 2020
In this paper, we address the following questions: What misconceptions do high school students exhibit in their first encounter with significance test problems through a repeated sampling approach? Which theory or framework could explain the presence and features of such patterns? With brief prior instruction on the use of Fathom software to…
Descriptors: High School Students, Misconceptions, Statistical Significance, Testing
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McAlevey, Lynn G.; Stent, Alan F. – International Journal of Mathematical Education in Science and Technology, 2018
The treatment of kurtosis in textbooks is both sparse and contradictory with applications rarely discussed. To address this, an easily understood definition of kurtosis is introduced and important applications are demonstrated. Two different approaches to teaching kurtosis are presented based on a financial application.
Descriptors: Statistical Distributions, Undergraduate Students, Probability, Statistical Data
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Cai, Tianji; Xia, Yiwei; Zhou, Yisu – Sociological Methods & Research, 2021
Analysts of discrete data often face the challenge of managing the tendency of inflation on certain values. When treated improperly, such phenomenon may lead to biased estimates and incorrect inferences. This study extends the existing literature on single-value inflated models and develops a general framework to handle variables with more than…
Descriptors: Statistical Distributions, Probability, Statistical Analysis, Statistical Bias
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Chaput, J. Scott; Crack, Timothy Falcon; Onishchenko, Olena – Journal of Statistics and Data Science Education, 2021
How accurately can final-year students majoring in statistics, physics, and finance label the vertical axis of a normal distribution, explain their label, identify units, and answer a question about the impact of horizontal-axis rescaling? Our survey finds that only 27 out of 148 students surveyed (i.e., 18.2%) could label the vertical axis of the…
Descriptors: Undergraduate Students, Advanced Students, Business Administration Education, Mathematics Skills
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Ranger, Jochen; Kuhn, Jörg Tobias; Ortner, Tuulia M. – Educational and Psychological Measurement, 2020
The hierarchical model of van der Linden is the most popular model for responses and response times in tests. It is composed of two separate submodels--one for the responses and one for the response times--that are joined at a higher level. The submodel for the response times is based on the lognormal distribution. The lognormal distribution is a…
Descriptors: Reaction Time, Tests, Statistical Distributions, Models
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von Oertzen, Timo; Schmiedek, Florian; Voelkle, Manuel C. – Journal of Intelligence, 2020
Properties of psychological variables at the mean or variance level can differ between persons and within persons across multiple time points. For example, cross-sectional findings between persons of different ages do not necessarily reflect the development of a single person over time. Recently, there has been an increased interest in the…
Descriptors: Cognitive Ability, Individual Differences, Statistical Analysis, Factor Analysis
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