Author

# Jacob Cohen

Other affiliations:Â University of York, York University

Bio: Jacob Cohen is an academic researcher from New York University. The author has contributed to research in topics: Sample size determination & One-way analysis of variance. The author has an hindex of 58, co-authored 110 publications receiving 135862 citations. Previous affiliations of Jacob Cohen include University of York & York University.

##### Papers published on a yearly basis

##### Papers

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York University

^{1}TL;DR: A convenient, although not comprehensive, presentation of required sample sizes is providedHere the sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests.

Abstract: One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.

38,291Â citations

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York University

^{1}TL;DR: In this article, the authors present a procedure for having two or more judges independently categorize a sample of units and determine the degree, significance, and significance of the units. But they do not discuss the extent to which these judgments are reproducible, i.e., reliable.

Abstract: CONSIDER Table 1. It represents in its formal characteristics a situation which arises in the clinical-social-personality areas of psychology, where it frequently occurs that the only useful level of measurement obtainable is nominal scaling (Stevens, 1951, pp. 2526), i.e. placement in a set of k unordered categories. Because the categorizing of the units is a consequence of some complex judgment process performed by a &dquo;two-legged meter&dquo; (Stevens, 1958), it becomes important to determine the extent to which these judgments are reproducible, i.e., reliable. The procedure which suggests itself is that of having two (or more) judges independently categorize a sample of units and determine the degree, significance, and

34,965Â citations

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01 Jan 1975

TL;DR: In this article, the Mathematical Basis for Multiple Regression/Correlation and Identification of the Inverse Matrix Elements is presented. But it does not address the problem of missing data.

Abstract: Contents: Preface. Introduction. Bivariate Correlation and Regression. Multiple Regression/Correlation With Two or More Independent Variables. Data Visualization, Exploration, and Assumption Checking: Diagnosing and Solving Regression Problems I. Data-Analytic Strategies Using Multiple Regression/Correlation. Quantitative Scales, Curvilinear Relationships, and Transformations. Interactions Among Continuous Variables. Categorical or Nominal Independent Variables. Interactions With Categorical Variables. Outliers and Multicollinearity: Diagnosing and Solving Regression Problems II. Missing Data. Multiple Regression/Correlation and Causal Models. Alternative Regression Models: Logistic, Poisson Regression, and the Generalized Linear Model. Random Coefficient Regression and Multilevel Models. Longitudinal Regression Methods. Multiple Dependent Variables: Set Correlation. Appendices: The Mathematical Basis for Multiple Regression/Correlation and Identification of the Inverse Matrix Elements. Determination of the Inverse Matrix and Applications Thereof.

29,764Â citations

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York University

^{1}TL;DR: The Kw provides for the incorpation of ratio-scaled degrees of disagreement (or agreement) to each of the cells of the k * k table of joi.

Abstract: A previously described coefficient of agreement for nominal scales, kappa, treats all disagreements equally. A generalization to weighted kappa (Kw) is presented. The Kw provides for the incorpation of ratio-scaled degrees of disagreement (or agreement) to each of the cells of the k * k table of joi

7,604Â citations

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TL;DR: The application of positron emis sion tomography (PEM) to the study of panic disorder was discussed in this paper, where a focal brain abnormal ity in panic disorder, a severe form of anxiety, was discussed.

Abstract: pression, Journal of Clinical Psychiatry, 51, 61-69 (1990). 11. L.R. Baxter, Jr., J.M. Schwartz, B.H. Guze, J.C. Mazziotta, M.P. Szuba, K. Bergman, A. Alazraki, C.E. Selin, H.K. Freng, P. Munford, and M.E. Phelps, Obsessive-compulsive disorder vs. Tourette's disorder: Differential function in subdivi sions of the neostriatum, paper presented at the an nual meeting of the American College of Neuropsy chopharmacology, San Juan, Puerto Rico (December 1991). 12. E.M. Reiman, M.E. Raichle, F.K. Butler, P. Herscovitch, and E. Robins, A focal brain abnormal ity in panic disorder, a severe form of anxiety, Na ture, 310, 683-685 (1984); E.M. Reiman, M.E. Ra ichle, E. Robins, F.K. Butler, P. Herscovitch, P. Fox, and J. Perlmutter, The application of positron emis sion tomography to the study of panic disorder, American Journal of Psychiatry, 143, 469-477 (1986); T.E. Nordahl, W.E. Semple, M. Gross, T.A. Mellman, M.B. Stein, P. Goyer, A.C. King, T.W. Uhde, and R.M. Cohen, Cerebral glucose metabolic differences in patients with panic disorder, Neuro psychopharmacology, 3, 261-272 (1990).

5,387Â citations

##### Cited by

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TL;DR: This article seeks to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating the many ways in which moderators and mediators differ, and delineates the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena.

Abstract: In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators.

80,095Â citations

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TL;DR: A general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies is presented and tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interob server agreement are developed as generalized kappa-type statistics.

Abstract: This paper presents a general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies. The procedure essentially involves the construction of functions of the observed proportions which are directed at the extent to which the observers agree among themselves and the construction of test statistics for hypotheses involving these functions. Tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interobserver agreement are developed as generalized kappa-type statistics. These procedures are illustrated with a clinical diagnosis example from the epidemiological literature.

64,109Â citations

01 Jan 1989

TL;DR: Regression analyses suggest that perceived ease of use may actually be a causal antecdent to perceived usefulness, as opposed to a parallel, direct determinant of system usage.

40,975Â citations

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[...]

York University

^{1}TL;DR: A convenient, although not comprehensive, presentation of required sample sizes is providedHere the sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests.

Abstract: One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.

38,291Â citations

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TL;DR: An overview of simple and multiple mediation is provided and three approaches that can be used to investigate indirect processes, as well as methods for contrasting two or more mediators within a single model are explored.

Abstract: Hypotheses involving mediation are common in the behavioral sciences. Mediation exists when a predictor affects a dependent variable indirectly through at least one intervening variable, or mediator. Methods to assess mediation involving multiple simultaneous mediators have received little attention in the methodological literature despite a clear need. We provide an overview of simple and multiple mediation and explore three approaches that can be used to investigate indirect processes, as well as methods for contrasting two or more mediators within a single model. We present an illustrative example, assessing and contrasting potential mediators of the relationship between the helpfulness of socialization agents and job satisfaction. We also provide SAS and SPSS macros, as well as Mplus and LISREL syntax, to facilitate the use of these methods in applications.

25,799Â citations