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Dorie, Vincent; Harada, Masataka; Carnegie, Nicole Bohme; Hill, Jennifer – Grantee Submission, 2016
When estimating causal effects, unmeasured confounding and model misspecification are both potential sources of bias. We propose a method to simultaneously address both issues in the form of a semi-parametric sensitivity analysis. In particular, our approach incorporates Bayesian Additive Regression Trees into a two-parameter sensitivity analysis…
Descriptors: Bayesian Statistics, Mathematical Models, Causal Models, Statistical Bias
Phillips, Lawrence; Pearl, Lisa – Cognitive Science, 2015
The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's "cognitive plausibility." We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition…
Descriptors: Language Acquisition, Models, Computational Linguistics, Credibility
Marina, Sarah; Davis-Hamilton, Zoya; Charmanski, Kara E. – Journal of Research Administration, 2015
Three studies were jointly conducted by the Office of Research Administration and Office of Proposal Development at Tufts University to evaluate the services within each respective office. The studies featured assessments that used, respectively, (1) quantitative metrics; (2) a quantitative satisfaction survey with limited qualitative questions;…
Descriptors: Research Administration, Evaluation Methods, Universities, Surveys
Kingston, Neal M.; Broaddus, Angela; Lao, Hongling – Measurement: Interdisciplinary Research and Perspectives, 2015
Briggs and Peck (2015) have written a thought-provoking article on the use of learning progressions in the design of vertical scales that support inferences about student growth. Organized learning models, including learning trajectories, learning progressions, and learning maps have been the subject of research for many years, but more recently…
Descriptors: Achievement Gains, Scaling, Scores, Inferences
Pearl, Judea – Sociological Methods & Research, 2015
This article summarizes a conceptual framework and simple mathematical methods of estimating the probability that one event was a necessary cause of another, as interpreted by lawmakers. We show that the fusion of observational and experimental data can yield informative bounds that, under certain circumstances, meet legal criteria of causation.…
Descriptors: Mathematical Models, Probability, Computation, Cognitive Mapping
Snijders, Tom A. B.; Steglich, Christian E. G. – Sociological Methods & Research, 2015
Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of…
Descriptors: Models, Statistical Analysis, Statistical Inference, Social Networks
Weller, Susan C. – Field Methods, 2015
This article presents a simple approach to making quick sample size estimates for basic hypothesis tests. Although there are many sources available for estimating sample sizes, methods are not often integrated across statistical tests, levels of measurement of variables, or effect sizes. A few parameters are required to estimate sample sizes and…
Descriptors: Sample Size, Statistical Analysis, Computation, Hypothesis Testing
Carsey, Thomas M.; Harden, Jeffrey J. – Journal of Political Science Education, 2015
Graduate students in political science come to the discipline interested in exploring important political questions, such as "What causes war?" or "What policies promote economic growth?" However, they typically do not arrive prepared to address those questions using quantitative methods. Graduate methods instructors must…
Descriptors: Monte Carlo Methods, Graduate Study, Methods Courses, Political Science
Turner, Stephen; Dabney, Alan R. – Teaching Statistics: An International Journal for Teachers, 2015
Statistical inference relies heavily on the concept of sampling distributions. However, sampling distributions are difficult to teach. We present a series of short animations that are story-based, with associated assessments. We hope that our contribution can be useful as a tool to teach sampling distributions in the introductory statistics…
Descriptors: Statistics, Statistical Analysis, Inferences, Sampling
Spalding, Thomas L.; Gagné, Christina L. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
Recent research shows that the judged likelihood of properties of modified nouns ("baby ducks have webbed feet") is reduced relative to judgments for unmodified nouns ("ducks have webbed feet"). This modification effect has been taken as evidence both for and against the idea that combined concepts automatically inherit…
Descriptors: Attribution Theory, Nouns, Inferences, Stereotypes
Elqayam, Shira; Thompson, Valerie A.; Wilkinson, Meredith R.; Evans, Jonathan St. B. T.; Over, David E. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
Humans have a unique ability to generate novel norms. Faced with the knowledge that there are hungry children in Somalia, we easily and naturally infer that we ought to donate to famine relief charities. Although a contentious and lively issue in metaethics, such inference from "is" to "ought" has not been systematically…
Descriptors: Inferences, Abstract Reasoning, Logical Thinking, Experiments
Briggs, Derek C.; Peck, Frederick A. – Measurement: Interdisciplinary Research and Perspectives, 2015
The concept of growth is at the foundation of the policy and practice around systems of educational accountability. It is also at the foundation of what teachers concern themselves with on a daily basis as they help children learn. Yet there is a disconnect between the criterion-referenced intuitions that parents and teachers have for what it…
Descriptors: Achievement Gains, Scaling, Scores, Inferences
Liu, In-mao; Chou, Ting-hsi – Journal of Cognition and Development, 2015
How likely is the glass to break, given that it is heated? The present study asks questions such as this with or without the premise "if the glass is heated, it breaks." A reduced problem (question without premise) measures the statistical dependency (conditional probability) of an event to occur, given that another has occurred. Such…
Descriptors: Logical Thinking, Cognitive Development, Probability, Inferences
Janssens, Leen; Drooghmans, Stephanie; Schaeken, Walter – Journal of Child Language, 2015
Conventional implicatures are omnipresent in daily life communication but experimental research on this topic is sparse, especially research with children. The aim of this study was to investigate if eight- to twelve-year-old children spontaneously make the conventional implicature induced by "but," "so," and…
Descriptors: Age Differences, Short Term Memory, Children, Preadolescents
Chung, Yeojin; Gelman, Andrew; Rabe-Hesketh, Sophia; Liu, Jingchen; Dorie, Vincent – Journal of Educational and Behavioral Statistics, 2015
When fitting hierarchical regression models, maximum likelihood (ML) estimation has computational (and, for some users, philosophical) advantages compared to full Bayesian inference, but when the number of groups is small, estimates of the covariance matrix (S) of group-level varying coefficients are often degenerate. One can do better, even from…
Descriptors: Regression (Statistics), Hierarchical Linear Modeling, Bayesian Statistics, Statistical Inference

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