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Leininger, Lindsey Jeanne; Kalil, Ariel – Journal of Policy Analysis and Management, 2008
Using data on approximately 2,000 low-income welfare recipients in a three-site random-assignment intervention conducted in the early 1990s (the NEWWS), we examine the role of cognitive and non-cognitive factors in moderating experimental impacts of an adult education training program for women who lacked a high school degree or GED at the time of…
Descriptors: Locus of Control, Females, Adult Education, Probability
Peer reviewedHenschke, Claudia I.; And Others – Multivariate Behavioral Research, 1974
The technique presented accomodates multiple populations and a mixture of variable types. It is based on the linear discriminant function and the sequential concept. Also presented is an example in which the technique is used to obtain the classification rule to predict the career choices of individuals based upon a mixture of variable types.…
Descriptors: Classification, Measurement Techniques, Predictor Variables, Probability
Peer reviewedGradstein, Mark – Journal of Educational Statistics, 1986
The purpose of this paper is to calculate the upper limit of the correlation between normal and dichotomous variables. An empirically obtained correlation should be evaluated in view of this limit, instead of the usual limit of Pearson correlation. (Author)
Descriptors: Correlation, Equations (Mathematics), Predictor Variables, Probability
Johnson, Matthew C.; Kercher, Glen A. – Journal of Interpersonal Violence, 2009
Victims of stalking often experience a number of negative psychological problems including such things as fear, symptoms of depression, and anger. However, research on factors that lead to these outcomes is limited. The goal of this study was to first identify distinct subgroups of stalking victims based on measures of psychological problems…
Descriptors: Probability, Depression (Psychology), Victims of Crime, Predictor Variables
James, John T.; Tichy, Karen L.; Collins, Alan; Schwob, John – Catholic Education: A Journal of Inquiry and Practice, 2008
This article examines a wide range of parish school indicators that can be used to predict long-term viability. The study reported in this article explored the relationship between demographic variables, financial variables, and parish grade school closures in the Archdiocese of Saint Louis. Specifically, this study investigated whether…
Descriptors: Catholic Schools, Sustainability, Predictor Variables, School Demography
Peer reviewedHaase, Richard F. – Educational and Psychological Measurement, 1976
Illustrates the use of multiple regression analysis for computing conditional probabilities of occurrence of events based on the functional relationship between a dependent response variate and one or more independent predictors. (RC)
Descriptors: Analysis of Variance, Multiple Regression Analysis, Predictor Variables, Probability
Weber, Elke U.; Shafir, Sharoni; Blais, Ann-Renee – Psychological Review, 2004
This article examines the statistical determinants of risk preference. In a meta-analysis of animal risk preference (foraging birds and insects), the coefficient of variation (CV), a measure of risk per unit of return, predicts choices far better than outcome variance, the risk measure of normative models. In a meta-analysis of human risk…
Descriptors: Probability, Risk, Animals, Predictor Variables
Waldmann, Michael R.; Hagmayer, York – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2005
The ability to derive predictions for the outcomes of potential actions from observational data is one of the hallmarks of true causal reasoning. We present four learning experiments with deterministic and probabilistic data showing that people indeed make different predictions from causal models, whose parameters were learned in a purely…
Descriptors: Competence, Observational Learning, Causal Models, Probability
Kobrin, Jennifer L. – College Board, 2007
The purpose of this research study was to determine benchmark scores on the SAT that predict a 65 percent probability or higher of getting a first-year college grade point average of either 2.7 or higher or 2.0 or higher, to use these benchmarks to describe the level of college readiness in the nation and in certain demographic subgroups, and to…
Descriptors: College Entrance Examinations, College Readiness, Benchmarking, Scores
Carrell, Scott E.; Malmstrom, Frederick V.; West, James E. – Journal of Human Resources, 2008
Using self-reported academic cheating from the classes of 1959 through 2002 at the three major United States military service academies (Air Force, Army, and Navy), we measure how peer cheating influences individual cheating behavior. We find higher levels of peer cheating result in a substantially increased probability that an individual will…
Descriptors: Military Service, College Students, Cheating, Peer Influence
Peer reviewedNewcomb, Andrew F.; Bukowski, William M. – Child Development, 1984
The stability of standard score and probability method sociometric group assignments was examined over a two-year period with an initial group of 334 fifth graders. Popular, neglected, and controversial groups evidenced low stability of group members over intervals of approximately 1, 6, 12, 18, and 24 months. (Author/RH)
Descriptors: Classification, Comparative Analysis, Longitudinal Studies, Preadolescents
Koplyay, Janos B.; And Others – 1972
The relationship between true ability (operationally defined as the number of items for which the examinee actually knew the correct answer) and the effects of guessing upon observed test variance was investigated. Three basic hypotheses were treated mathematically: there is no functional relationship between true ability and guessing success;…
Descriptors: Guessing (Tests), Predictor Variables, Probability, Scoring
Peer reviewedMcSweeney, Maryellen; Schmidt, William H. – Journal of Educational Statistics, 1977
The relationship between quantitative predictor variables and the probability of occurrence of one or more levels of a qualitative criterion variable can be analyzed by quantal response techniques. This paper presents and discusses two quantal response models, comparing them to multiple linear regression and discriminant analysis. (Author/JKS)
Descriptors: Discriminant Analysis, Mathematical Models, Multiple Regression Analysis, Predictor Variables
Dupere, Veronique; Lacourse, Eric; Willms, J. Douglas; Vitaro, Frank; Tremblay, Richard E. – Journal of Abnormal Child Psychology, 2007
Because youth gangs tend to cluster in disadvantaged neighborhoods, adolescents living in such neighborhoods are more likely to encounter opportunities to join youth gangs. However, in the face of these opportunities, not all adolescents respond in the same manner. Those with preexisting psychopathic tendencies might be especially likely to join.…
Descriptors: Foreign Countries, Probability, Adolescents, Neighborhoods
Jorgensen, Shirley; Fichten, Catherine; Havel, Alice – Online Submission, 2009
The main aim of this study was to gain a better understanding of why students abandon their studies, or perform less well than expected given their high school grades, and to develop predictive models that can help identify those students most at-risk at the time they enter college. This will allow teachers and those responsible for student…
Descriptors: High School Students, Grades (Scholastic), Academic Failure, Profiles

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