Publication Date
| In 2026 | 0 |
| Since 2025 | 1 |
| Since 2022 (last 5 years) | 3 |
| Since 2017 (last 10 years) | 82 |
| Since 2007 (last 20 years) | 487 |
Descriptor
| Predictor Variables | 548 |
| Statistical Significance | 548 |
| Statistical Analysis | 197 |
| Correlation | 190 |
| Foreign Countries | 127 |
| Gender Differences | 114 |
| Academic Achievement | 108 |
| Regression (Statistics) | 107 |
| Multiple Regression Analysis | 99 |
| Scores | 94 |
| Questionnaires | 91 |
| More ▼ | |
Source
Author
| Borich, Gary D. | 3 |
| Pohlmann, John T. | 3 |
| Davis, Dawn H. | 2 |
| Fass-Holmes, Barry | 2 |
| Gordon, Howard R. D. | 2 |
| Huberty, Carl J. | 2 |
| Jaciw, Andrew | 2 |
| Pascarella, Ernest T. | 2 |
| Rapaport, Amie | 2 |
| Soria, Krista | 2 |
| Thompson, Bruce | 2 |
| More ▼ | |
Publication Type
Education Level
Audience
| Researchers | 6 |
| Policymakers | 2 |
| Teachers | 2 |
| Administrators | 1 |
Location
| Turkey | 21 |
| Texas | 19 |
| Jordan | 15 |
| Saudi Arabia | 11 |
| California | 10 |
| United States | 10 |
| North Carolina | 8 |
| Australia | 7 |
| Canada | 7 |
| Illinois | 7 |
| Maryland | 7 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
| Meets WWC Standards with or without Reservations | 1 |
| Does not meet standards | 5 |
Schumacher, Julie Raeder – ProQuest LLC, 2009
A journal club is defined as a group of individuals who meet regularly to discuss current trends in literature and have been advocated to bridge the gap of research and practice. With the popularity of the Internet, there are a variety of tools available for online learning through journal clubs including asynchronous discussions, which the…
Descriptors: Learning Strategies, Learning Processes, Communities of Practice, Clubs
Strang, Kenneth David – Practical Assessment, Research & Evaluation, 2009
This paper discusses how a seldom-used statistical procedure, recursive regression (RR), can numerically and graphically illustrate data-driven nonlinear relationships and interaction of variables. This routine falls into the family of exploratory techniques, yet a few interesting features make it a valuable compliment to factor analysis and…
Descriptors: Multicultural Education, Computer Software, Multiple Regression Analysis, Multidimensional Scaling
Peer reviewedRogosa, David – Educational and Psychological Measurement, 1981
The form of the Johnson-Neyman region of significance is shown to be determined by the statistic for testing the null hypothesis that the population within-group regressions are parallel. Results are obtained for both simultaneous and nonsimultaneous regions of significance. (Author)
Descriptors: Hypothesis Testing, Mathematical Models, Predictor Variables, Regression (Statistics)
Collins, Kathleen M. T.; Onwuegbuzie, Anthony J.; Jiao, Qun G. – Reading Psychology, 2008
The present study examined the relationship between reading ability (i.e., reading comprehension and reading vocabulary) and academic procrastination among 120 African American graduate students. A canonical correlation analysis revealed statistically significant and practically significant multivariate relationships between these two reading…
Descriptors: Research Papers (Students), Reading Assignments, Graduate Students, Reading Comprehension
Peer reviewedGocka, Edward F. – Educational and Psychological Measurement, 1974
Focuses on the procedures available for substituting a special predictive coding method for some of the more complex general regression procedures. (Author)
Descriptors: Analysis of Variance, Codification, Correlation, Predictor Variables
Lee, Wan-Fung; Bulcock, Jeffrey Wilson – 1979
The purposes of this study are: (1) to demonstrate the superiority of simple ridge regression over ordinary least squares regression through theoretical argument and empirical example; (2) to modify ridge regression through use of the variance normalization criterion; and (3) to demonstrate the superiority of simple ridge regression based on the…
Descriptors: Longitudinal Studies, Multivariate Analysis, Path Analysis, Predictor Variables
Peer reviewedPohlmann, John T. – Multiple Linear Regression Viewpoints, 1979
The type I error rate in stepwise regression analysis deserves serious consideration by researchers. The problem-wide error rate is the probability of selecting any variable when all variables have population regression weights of zero. Appropriate significance tests are presented and a Monte Carlo experiment is described. (Author/CTM)
Descriptors: Correlation, Error Patterns, Multiple Regression Analysis, Predictor Variables
Peer reviewedBerry, Kenneth J.; Mielke, Paul W., Jr. – Educational and Psychological Measurement, 1992
A generalized measure of association and an associated test of significance are presented for nominal independent variables in which any number or combination of interval, ordinal, or nominal dependent variables can be analyzed. A permutation test of significance is provided for the new measure. (SLD)
Descriptors: Correlation, Equations (Mathematics), Mathematical Models, Multivariate Analysis
Peer reviewedGordon, Howard R. D. – Journal of Vocational Education Research, 2001
A sample of 113 American Vocational Education Research Association members (93% with doctorates, 67% with more than 15 years of research experience) disagreed that statistical significance tests should be banned; were less likely to realize that stepwise methods do not identify the best predictor set; and recognized that studies with…
Descriptors: Educational Research, Predictor Variables, Researchers, Statistical Significance
Yoon, Jina – 1995
Contrary to popular opinion, significance testing does not inform the researcher of the likelihood of the replication of results from current research findings. Result replicability has been ignored by researchers because of an overreliance on significance testing. Several alternatives have been offered to provide the researcher with more…
Descriptors: Evaluation Methods, Predictor Variables, Regression (Statistics), Research Methodology
PDF pending restorationMalgady, Robert G. – 1975
Common applications of the part correlation coefficient are in causal regression models and estimation of suppressor variable effects. However, there is no statistical test of the significance of the difference between a zero-order correlation and a part correlation, nor between a pair of part correlations. Hotelling's t is used for contrasting:…
Descriptors: Correlation, Mathematical Models, Multiple Regression Analysis, Predictor Variables
Moradi, Saeid; Khalkhali, Ali – Multicultural Education & Technology Journal, 2008
Purpose: The purpose of this paper is to evaluate the level of ICT (information and communication technologies) integration and usage in teachers, curricula in Iranian schools. Design/methodology/approach: The data for the study were gathered through a questionnaire administered to 160 respondents who were school teachers. In total, 154…
Descriptors: Foreign Countries, Computer Uses in Education, Statistical Significance, Correlation
Peer reviewedTakane, Yoshio; Cramer, Elliott M. – Multivariate Behavioral Research, 1975
This paper considers the case of two predictor variables. Figures are obtained which show the regions of significance of joint regression coefficients, regression coefficients considered separately, and the multiple correlation. The intersection of these regions of significance and non-significance illustrates how the various apparent…
Descriptors: Correlation, Hypothesis Testing, Maps, Multiple Regression Analysis
Peer reviewedMichalos, Alex C. – Social Indicators Research, 2004
The aim of this essay is to build a bridge between two intersecting areas of research, social indicators research on the one hand and health-related quality of life research on the other. The first substantive section of the paper introduces key concepts and definitions in the social indicators research tradition, e.g., social indicators,…
Descriptors: Psychological Patterns, Social Indicators, Researchers, Statistical Significance
Peer reviewedThompson, Bruce; Borrello, Gloria M. – Educational and Psychological Measurement, 1985
Multiple regression analysis is frequently being employed in experimental and non-experimental research. However, when data include predictor variables that are correlated, some regression results can become difficult to interpret. This paper presents a study to provide a demonstration that structure coefficients may be useful in these cases.…
Descriptors: Correlation, Multiple Regression Analysis, Multivariate Analysis, Predictor Variables

Direct link
