NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 22 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
David Voas; Laura Watt – Teaching Statistics: An International Journal for Teachers, 2025
Binary logistic regression is one of the most widely used statistical tools. The method uses odds, log odds, and odds ratios, which are difficult to understand and interpret. Understanding of logistic regression tends to fall down in one of three ways: (1) Many students and researchers come to believe that an odds ratio translates directly into…
Descriptors: Statistics, Statistics Education, Regression (Statistics), Misconceptions
Peer reviewed Peer reviewed
Direct linkDirect link
Ioana-Elena Oana; Carsten Q. Schneider – Sociological Methods & Research, 2024
The robustness of qualitative comparative analysis (QCA) results features high on the agenda of methodologists and practitioners. This article aims at advancing this debate on several fronts. First, in line with the extant literature, we take a comprehensive view on robustness arguing that decisions on calibration, consistency, and frequency…
Descriptors: Robustness (Statistics), Qualitative Research, Comparative Analysis, Decision Making
Peer reviewed Peer reviewed
Direct linkDirect link
Victoria Savalei; Yves Rosseel – Structural Equation Modeling: A Multidisciplinary Journal, 2022
This article provides an overview of different computational options for inference following normal theory maximum likelihood (ML) estimation in structural equation modeling (SEM) with incomplete normal and nonnormal data. Complete data are covered as a special case. These computational options include whether the information matrix is observed or…
Descriptors: Structural Equation Models, Computation, Error of Measurement, Robustness (Statistics)
Peer reviewed Peer reviewed
Direct linkDirect link
Tomek, Sara; Robinson, Cecil – Measurement: Interdisciplinary Research and Perspectives, 2021
Typical longitudinal growth models assume constant functional growth over time. However, there are often conditions where trajectories may not be constant over time. For example, trajectories of psychological behaviors may vary based on a participant's age, or conversely, participants may experience an intervention that causes trajectories to…
Descriptors: Growth Models, Statistical Analysis, Hierarchical Linear Modeling, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
Kuha, Jouni; Mills, Colin – Sociological Methods & Research, 2020
It is widely believed that regression models for binary responses are problematic if we want to compare estimated coefficients from models for different groups or with different explanatory variables. This concern has two forms. The first arises if the binary model is treated as an estimate of a model for an unobserved continuous response and the…
Descriptors: Comparative Analysis, Regression (Statistics), Research Problems, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
Koster, Jeremy; Leckie, George; Aven, Brandy – Field Methods, 2020
The multilevel social relations model (SRM) is a commonly used statistical method for the analysis of social networks. In this article and accompanying supplemental materials, we demonstrate the estimation and interpretation of the SRM using Stat-JR software. Multiple software templates permit the analysis of different response types, including…
Descriptors: Statistical Analysis, Computer Software, Hierarchical Linear Modeling, Social Networks
Peer reviewed Peer reviewed
Direct linkDirect link
Swank, Jacqueline M.; Mullen, Patrick R. – Measurement and Evaluation in Counseling and Development, 2017
The article serves as a guide for researchers in developing evidence of validity using bivariate correlations, specifically construct validity. The authors outline the steps for calculating and interpreting bivariate correlations. Additionally, they provide an illustrative example and discuss the implications.
Descriptors: Correlation, Construct Validity, Guidelines, Data Interpretation
Peer reviewed Peer reviewed
Direct linkDirect link
Ames, Allison; Myers, Aaron – Educational Measurement: Issues and Practice, 2019
Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model-data fit models…
Descriptors: Bayesian Statistics, Psychometrics, Models, Predictive Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Slade, David J. – Journal of Chemical Education, 2017
The first-semester introductory organic chemistry laboratory has been adapted to include mini postlab assignments that students must complete correctly, through as many attempts as prove to be necessary. The use of multiple drafts of writing assignments is a standard approach to improving writing, so the system was designed to require drafts for…
Descriptors: Organic Chemistry, Introductory Courses, Science Laboratories, College Science
Lohrengel, C. Frederick, II.; Larson, Paul R. – Geography Teacher, 2017
National Geography Standard 1 requires that students learn:"How to use maps and other geographic representations, geospatial technologies, and spatial thinking to understand and communicate information" (Heffron and Downs 2012). These concepts have real-world applicability. For example, elevation contour maps are common in many…
Descriptors: Data Collection, Data Interpretation, Map Skills, Physical Geography
Peer reviewed Peer reviewed
Direct linkDirect link
Tutz, Gerhard; Berger, Moritz – Journal of Educational and Behavioral Statistics, 2016
Heterogeneity in response styles can affect the conclusions drawn from rating scale data. In particular, biased estimates can be expected if one ignores a tendency to middle categories or to extreme categories. An adjacent categories model is proposed that simultaneously models the content-related effects and the heterogeneity in response styles.…
Descriptors: Response Style (Tests), Rating Scales, Data Interpretation, Statistical Bias
Peer reviewed Peer reviewed
Direct linkDirect link
Strayer, Jeremy F.; Edwards, Michael Todd – Mathematics Teacher, 2015
A news story claiming that the cream filling of a popular "double" cream sandwich cookie is not really "double" went viral in fall 2013. A high school mathematics teacher posted a blog entry describing how he and his students measured 20 cookies, analyzed the data, and concluded that the double cream cookies had only 1.86 times…
Descriptors: Media Literacy, News Media, Mathematics Education, Statistics
Pasley, Joan D.; Trygstad, Peggy J.; Banilower, Eric R. – Horizon Research, Inc., 2016
The Next Generation Science Standards (NGSS) are composed of three intertwined dimensions--disciplinary core ideas, science and engineering practices, and crosscutting concepts--that provide a foundation for what students should know and be able to do at various grade levels. The eight science practices outlined in the NGSS are critical components…
Descriptors: Program Implementation, Science Education, Elementary Secondary Education, Scientific Principles
Peer reviewed Peer reviewed
Direct linkDirect link
Boose, David L. – Journal of College Science Teaching, 2014
Quantitative reasoning is a key intellectual skill, applicable across disciplines and best taught in the context of authentic, relevant problems. Here, I describe and assess a laboratory exercise that has students calculate their "carbon footprint" and evaluate the impacts of various behavior choices on that footprint. Students gather…
Descriptors: Nonmajors, Statistical Analysis, Data Collection, Computation
Peer reviewed Peer reviewed
Direct linkDirect link
Sneider, Cary; Stephenson, Chris; Schafer, Bruce; Flick, Larry – Science Teacher, 2014
A "Framework for K-12 Science Education" identified eight practices as "essential elements of the K-12 science and engineering curriculum" (NRC 2012, p. 49). Most of the practices, such as Developing and Using Models, Planning and Carrying Out Investigations, and Analyzing and Interpreting Data, are well known among science…
Descriptors: High School Students, Secondary School Science, Thinking Skills, Computation
Previous Page | Next Page ยป
Pages: 1  |  2