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Showing all 13 results Save | Export
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Young, Cristobal – Sociological Methods & Research, 2019
The commenter's proposal may be a reasonable method for addressing uncertainty in predictive modeling, where the goal is to predict "y." In a treatment effects framework, where the goal is causal inference by conditioning-on-observables, the commenter's proposal is deeply flawed. The proposal (1) ignores the definition of…
Descriptors: Causal Models, Predictor Variables, Research Methodology, Ambiguity (Context)
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Widaman, Keith F. – Measurement: Interdisciplinary Research and Perspectives, 2014
Latent variable structural equation modeling has become the analytic method of choice in many domains of research in psychology and allied social sciences. One important aspect of a latent variable model concerns the relations hypothesized to hold between latent variables and their indicators. The most common specification of structural equation…
Descriptors: Structural Equation Models, Predictor Variables, Educational Research, Causal Models
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Nicole Bohme Carnegie; Masataka Harada; Jennifer L. Hill – Journal of Research on Educational Effectiveness, 2016
A major obstacle to developing evidenced-based policy is the difficulty of implementing randomized experiments to answer all causal questions of interest. When using a nonexperimental study, it is critical to assess how much the results could be affected by unmeasured confounding. We present a set of graphical and numeric tools to explore the…
Descriptors: Randomized Controlled Trials, Simulation, Evidence Based Practice, Barriers
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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
Lo, Yun-Jia – ProQuest LLC, 2012
In educational research, a randomized controlled trial is the best design to eliminate potential selection bias in a sample to support valid causal inferences, but it is not always possible in educational research because of financial, ethical, and logistical constrains. One alternative solution is use of the propensity score (PS) methods.…
Descriptors: Educational Research, Probability, Scores, Research Methodology
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Connelly, Brian S.; Sackett, Paul R.; Waters, Shonna D. – Personnel Psychology, 2013
Organizational and applied sciences have long struggled with improving causal inference in quasi-experiments. We introduce organizational researchers to propensity scoring, a statistical technique that has become popular in other applied sciences as a means for improving internal validity. Propensity scoring statistically models how individuals in…
Descriptors: Quasiexperimental Design, Control Groups, Inferences, Research Methodology
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T. R. Kratochwill; J. Hitchcock; R. H. Horner; J. R. Levin; S. L. Odom; D. M Rindskopf; W. R. Shadish – What Works Clearinghouse, 2010
In an effort to expand the pool of scientific evidence available for review, the What Works Clearinghouse (WWC) assembled a panel of national experts in single-case design (SCD) and analysis to draft SCD Standards. SCDs are adaptations of interrupted time-series designs and can provide a rigorous experimental evaluation of intervention effects.…
Descriptors: Research Methodology, Standards, Causal Models, Intervention
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Pohlmann, John T. – Mid-Western Educational Researcher, 1993
Nonlinear relationships and latent variable assumptions can lead to serious specification errors in structural models. A quadratic relationship, described by a linear structural model with a latent variable, is shown to have less predictive validity than a simple manifest variable regression model. Advocates the use of simpler preliminary…
Descriptors: Causal Models, Error of Measurement, Predictor Variables, Research Methodology
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Schumacker, Randall E. – Mid-Western Educational Researcher, 1993
Structural equation models merge multiple regression, path analysis, and factor analysis techniques into a single data analytic framework. Measurement models are developed to define latent variables, and structural equations are then established among the latent variables. Explains the development of these models. (KS)
Descriptors: Causal Models, Data Analysis, Error of Measurement, Factor Analysis
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Hsu, Wen-Kai K.; Huang, Show-Hui S. – Journal of Educational Computing Research, 2006
The purpose of this article is to discuss determinants of computer self-efficacy from the perspective of participant internal learning motivations and external learning environments. The former consisted of three motivations--interest, trend, and employment--while the latter comprised two environments--home and school. Through an intermediate…
Descriptors: Family Environment, Educational Environment, Computer Uses in Education, Causal Models
Schmitt, Neal – 1991
Detailed methodology used to evaluate a causal model of school environment is presented in this report. The model depicts societal features that influence school district values and organizational characteristics, which in turn influence school operations and personnel attitudes and values. These school variables affect school community members'…
Descriptors: Analysis of Variance, Causal Models, Correlation, Educational Environment
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Carr, James E.; Austin, John – Teaching of Psychology, 1997
Provides a brief overview of single-subject research designs. This method exercises its power by examining changes in single subjects' responses over time across experimental conditions. Describes a classroom project in which students collect repeated measures of their own behavior and graph the data. (MJP)
Descriptors: Causal Models, Data Collection, Data Interpretation, Demonstrations (Educational)
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers