Publication Date
In 2025 | 1 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 7 |
Since 2006 (last 20 years) | 11 |
Descriptor
Causal Models | 13 |
Statistical Analysis | 13 |
Validity | 13 |
Regression (Statistics) | 4 |
Research Methodology | 4 |
Comparative Analysis | 3 |
Correlation | 3 |
Evaluation Methods | 3 |
Measurement | 3 |
Academic Achievement | 2 |
Monte Carlo Methods | 2 |
More ▼ |
Source
Author
Abd-El-Khalick, Fouad | 1 |
Cadogan, John W. | 1 |
Cook, Thomas D. | 1 |
Dasgupta, Tirthankar | 1 |
Deke, John | 1 |
Ding, Peng | 1 |
Erb, Christopher D. | 1 |
Fernbach, Philip M. | 1 |
Guyon, Hervé | 1 |
Imbens, Guido W. | 1 |
Kisbu-Sakarya, Yasemin | 1 |
More ▼ |
Publication Type
Journal Articles | 8 |
Reports - Descriptive | 6 |
Reports - Research | 5 |
Opinion Papers | 2 |
Guides - General | 1 |
Information Analyses | 1 |
Reports - Evaluative | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Elementary Secondary Education | 1 |
Higher Education | 1 |
Postsecondary Education | 1 |
Audience
Researchers | 4 |
Practitioners | 1 |
Teachers | 1 |
Location
Qatar | 1 |
Rhode Island | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Reichardt, Charles S. – American Journal of Evaluation, 2022
Evaluators are often called upon to assess the effects of programs. To assess a program effect, evaluators need a clear understanding of how a program effect is defined. Arguably, the most widely used definition of a program effect is the counterfactual one. According to the counterfactual definition, a program effect is the difference between…
Descriptors: Program Evaluation, Definitions, Causal Models, Evaluation Methods
Mahmoud M. S. Abdallah – Online Submission, 2025
This guide offers a comprehensive handbook to scientific research methodology and experimental design, specifically for novice MA and PhD researchers in Education and Language Learning (TESOL/TEFL). It establishes scientific research as a systematic, objective inquiry focused on identifying cause-and-effect relationships through empirical data.…
Descriptors: Scientific Research, Research Methodology, Research Design, Second Language Learning
Cadogan, John W.; Lee, Nick – Measurement: Interdisciplinary Research and Perspectives, 2016
In this commentary from Issue 14, n3, authors John Cadogan and Nick Lee applaud the paper by Aguirre-Urreta, Rönkkö, and Marakas "Measurement: Interdisciplinary Research and Perspectives", 14(3), 75-97 (2016), since their explanations and simulations work toward demystifying causal indicator models, which are often used by scholars…
Descriptors: Causal Models, Measurement, Validity, Statistical Analysis
Ding, Peng; Dasgupta, Tirthankar – Grantee Submission, 2017
Fisher randomization tests for Neyman's null hypothesis of no average treatment effects are considered in a finite population setting associated with completely randomized experiments with more than two treatments. The consequences of using the F statistic to conduct such a test are examined both theoretically and computationally, and it is argued…
Descriptors: Statistical Analysis, Statistical Inference, Causal Models, Error Patterns
Guyon, Hervé; Tensaout, Mouloud – Measurement: Interdisciplinary Research and Perspectives, 2016
In this article, the authors extend the results of Aguirre-Urreta, Rönkkö, and Marakas (2016) concerning the omission of a relevant causal indicator by testing the validity of the assumption that causal indicators are entirely superfluous to the measurement model and discuss the implications for measurement theory. Contrary to common wisdom…
Descriptors: Causal Models, Structural Equation Models, Formative Evaluation, Measurement
Tang, Yang; Cook, Thomas D.; Kisbu-Sakarya, Yasemin – Society for Research on Educational Effectiveness, 2015
Regression discontinuity design (RD) has been widely used to produce reliable causal estimates. Researchers have validated the accuracy of RD design using within study comparisons (Cook, Shadish & Wong, 2008; Cook & Steiner, 2010; Shadish et al, 2011). Within study comparisons examines the validity of a quasi-experiment by comparing its…
Descriptors: Pretests Posttests, Statistical Bias, Accuracy, Regression (Statistics)
Said, Ziad; Summers, Ryan; Abd-El-Khalick, Fouad; Wang, Shuai – International Journal of Science Education, 2016
This study assessed students' attitudes toward science in Qatar. A cross-sectional, nationwide probability sample representing all students enrolled in grades 3 through 12 in the various types of schools in Qatar completed the "Arabic Speaking Students' Attitudes toward Science Survey" (ASSASS). The validity and reliability of the…
Descriptors: Scientific Attitudes, Arabs, Student Attitudes, Case Studies
Lei, Wu; Qing, Fang; Zhou, Jin – International Journal of Distance Education Technologies, 2016
There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…
Descriptors: Causal Models, Attribution Theory, Correlation, Evaluation Methods
Fernbach, Philip M.; Erb, Christopher D. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2013
The authors propose and test a causal model theory of reasoning about conditional arguments with causal content. According to the theory, the acceptability of modus ponens (MP) and affirming the consequent (AC) reflect the conditional likelihood of causes and effects based on a probabilistic causal model of the scenario being judged. Acceptability…
Descriptors: Causal Models, Logical Thinking, Statistical Analysis, Validity
Imbens, Guido W. – Psychological Methods, 2010
In Shadish (2010) and West and Thoemmes (2010), the authors contrasted 2 approaches to causality. The first originated in the psychology literature and is associated with work by Campbell (e.g., Shadish, Cook, & Campbell, 2002), and the second has its roots in the statistics literature and is associated with work by Rubin (e.g., Rubin, 2006). In…
Descriptors: Economics, Research Methodology, Causal Models, Inferences
Schochet, Peter Z.; Puma, Mike; Deke, John – National Center for Education Evaluation and Regional Assistance, 2014
This report summarizes the complex research literature on quantitative methods for assessing how impacts of educational interventions on instructional practices and student learning differ across students, educators, and schools. It also provides technical guidance about the use and interpretation of these methods. The research topics addressed…
Descriptors: Statistical Analysis, Evaluation Methods, Educational Research, Intervention
O'Neil, John; And Others – 1994
Production-function analysis, a correlation-based analysis, has been used for years to evaluate whether resources deposited into the educational process yielded a definitive result. For example, it has been used in several state cases as a measure of equity in educational funding. This paper is of the opinion that correlation-based analyses are…
Descriptors: Academic Achievement, Causal Models, Correlation, Costs

Maeshiro, Asatoshi – Journal of Economic Education, 1996
Rectifies the unsatisfactory textbook treatment of the finite-sample proprieties of estimators of regression models with a lagged dependent variable and autocorrelated disturbances. Maintains that the bias of the ordinary least squares estimator is determined by the dynamic and correlation effects. (MJP)
Descriptors: Causal Models, Correlation, Economics Education, Heuristics