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Cai, Zhiqiang; Li, Hiyiang; Hu, Xiangen; Graesser, Art – Grantee Submission, 2016
This paper provides an alternative way of document representation by treating topic probabilities as a vector representation for words and representing a document as a combination of the word vectors. A comparison on summary data shows that this representation is more effective in document classification. [This paper was published in:…
Descriptors: Probability, Natural Language Processing, Models, Automation
Brusco, Michael J.; Cradit, J. Dennis; Steinley, Douglas; Fox, Gavin L. – Multivariate Behavioral Research, 2008
Clusterwise linear regression is a multivariate statistical procedure that attempts to cluster objects with the objective of minimizing the sum of the error sums of squares for the within-cluster regression models. In this article, we show that the minimization of this criterion makes no effort to distinguish the error explained by the…
Descriptors: Regression (Statistics), Models, Research Methodology, Multivariate Analysis
Gershman, Samuel J.; Blei, David M.; Niv, Yael – Psychological Review, 2010
A. Redish et al. (2007) proposed a reinforcement learning model of context-dependent learning and extinction in conditioning experiments, using the idea of "state classification" to categorize new observations into states. In the current article, the authors propose an interpretation of this idea in terms of normative statistical inference. They…
Descriptors: Conditioning, Statistical Inference, Inferences, Bayesian Statistics
Lee, Max Kueiming; Ou, Sheue-Jen – Forum on Public Policy Online, 2008
Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…
Descriptors: Language Acquisition, Network Analysis, Topology, Language Research
Hedges, Larry V. – Journal of Educational and Behavioral Statistics, 2007
A common mistake in analysis of cluster randomized trials is to ignore the effect of clustering and analyze the data as if each treatment group were a simple random sample. This typically leads to an overstatement of the precision of results and anticonservative conclusions about precision and statistical significance of treatment effects. This…
Descriptors: Statistical Significance, Computation, Cluster Grouping, Statistics
Wilkerson, Kevin; Bellini, James – Journal of Counseling & Development, 2006
This study investigated the demographic, intrapersonal, and organizational factors associated with burnout among a population of school counselors in the northeastern United States (n = 78). Three hierarchical regression analyses were completed to determine the amount of variance that each cluster contributed to the 3 subscales on the Maslach…
Descriptors: Burnout, School Counselors, Demography, Multiple Regression Analysis

Als, Heidelise – Monographs of the Society for Research in Child Development, 1978
Describes the conceptual model of newborn organization underlying the Brazelton Neonatal Behavioral Assessment Scale (NBAS). Argues that while the NBAS allows for the identification of an individual's behavioral repertoire, attempts to synthesize the resulting data have been plagued with difficulties. Briefly outlines an alternative model for…
Descriptors: Child Development, Cluster Grouping, Conceptual Schemes, Infant Behavior