NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 12 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Parkkinen, Veli-Pekka; Baumgartner, Michael – Sociological Methods & Research, 2023
In recent years, proponents of configurational comparative methods (CCMs) have advanced various dimensions of robustness as instrumental to model selection. But these robustness considerations have not led to computable robustness measures, and they have typically been applied to the analysis of real-life data with unknown underlying causal…
Descriptors: Robustness (Statistics), Comparative Analysis, Causal Models, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Thiem, Alrik – Sociological Methods & Research, 2022
Qualitative Comparative Analysis (QCA) is a relatively young method of causal inference that continues to diffuse across the social sciences. However, recent methodological research has found the conservative (QCA-CS) and the intermediate solution type (QCA-IS) of QCA to fail fundamental tests of correctness. Even under conditions otherwise ideal…
Descriptors: Comparative Analysis, Causal Models, Inferences, Risk
Peer reviewed Peer reviewed
Direct linkDirect link
Hertog, Steffen – Sociological Methods & Research, 2023
In mixed methods approaches, statistical models are used to identify "nested" cases for intensive, small-n investigation for a range of purposes, including notably the examination of causal mechanisms. This article shows that under a commonsense interpretation of causal effects, large-n models allow no reliable conclusions about effect…
Descriptors: Case Studies, Generalization, Prediction, Mixed Methods Research
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Weidlich, Joshua; Gaševic, Dragan; Drachsler, Hendrik – Journal of Learning Analytics, 2022
As a research field geared toward understanding and improving learning, Learning Analytics (LA) must be able to provide empirical support for causal claims. However, as a highly applied field, tightly controlled randomized experiments are not always feasible nor desirable. Instead, researchers often rely on observational data, based on which they…
Descriptors: Causal Models, Inferences, Learning Analytics, Comparative Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Wing, Coady; Bello-Gomez, Ricardo A. – American Journal of Evaluation, 2018
Treatment effect estimates from a "regression discontinuity design" (RDD) have high internal validity. However, the arguments that support the design apply to a subpopulation that is narrower and usually different from the population of substantive interest in evaluation research. The disconnect between RDD population and the…
Descriptors: Regression (Statistics), Research Design, Validity, Evaluation Methods
Peer reviewed Peer reviewed
Direct linkDirect link
Bao, Lei; Koenig, Kathleen; Xiao, Yang; Fritchman, Joseph; Zhou, Shaona; Chen, Cheng – Physical Review Physics Education Research, 2022
Abilities in scientific thinking and reasoning have been emphasized as core areas of initiatives, such as the Next Generation Science Standards or the College Board Standards for College Success in Science, which focus on the skills the future will demand of today's students. Although there is rich literature on studies of how these abilities…
Descriptors: Physics, Science Instruction, Teaching Methods, Thinking Skills
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Frank, Kenneth A.; Maroulis, Spiro J.; Duong, Minh Q.; Kelcey, Benjamin M. – Educational Evaluation and Policy Analysis, 2013
We contribute to debate about causal inferences in educational research in two ways. First, we quantify how much bias there must be in an estimate to invalidate an inference. Second, we utilize Rubin's causal model to interpret the bias necessary to invalidate an inference in terms of sample replacement. We apply our analysis to an inference…
Descriptors: Causal Models, Inferences, Research Methodology, Robustness (Statistics)
Peer reviewed Peer reviewed
Direct linkDirect link
Love, Edwin; Stelling, Pete – Marketing Education Review, 2012
The reaction that occurs when Mentos are added to bottled soft drinks has become a staple demonstration in earth science courses to explain how volcanoes erupt. This paper presents how this engaging exercise can be used in a marketing research course to provide hands-on experience with problem formation, hypothesis testing, and causal research. A…
Descriptors: Marketing, Research, Comparative Analysis, Experiments
Peer reviewed Peer reviewed
Direct linkDirect link
Coffman, Donna L. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
Mediation is usually assessed by a regression-based or structural equation modeling (SEM) approach that we refer to as the classical approach. This approach relies on the assumption that there are no confounders that influence both the mediator, "M", and the outcome, "Y". This assumption holds if individuals are randomly…
Descriptors: Structural Equation Models, Simulation, Regression (Statistics), Probability
Peer reviewed Peer reviewed
Direct linkDirect link
Stuart, Elizabeth A. – Educational Researcher, 2007
Education researchers, practitioners, and policymakers alike are committed to identifying interventions that teach students more effectively. Increased emphasis on evaluation and accountability has increased desire for sound evaluations of these interventions; and at the same time, school-level data have become increasingly available. This article…
Descriptors: Research Methodology, Computation, Causal Models, Intervention
Peer reviewed Peer reviewed
Yunker, James A. – Journal of Economic Education, 1998
Describes a general equilibrium model that fills the gap between the general function models described in price-theory textbooks and the numerical practice of general equilibrium analysis used in contemporary policy assessment. This model uses explicit mathematical forms but general parameter values. Includes graphs and statistical tables. (MJP)
Descriptors: Business Cycles, Causal Models, Comparative Analysis, Economics