Regression References

Books

• Cohen, J., and Cohen, P. (1975). Applied Multiple Regression and Correlation Analysis for the Behavioral Sciences, Hillsdale, New Jersey: Lawrence Erlbaum Associates.
• R. D. Cook and S. Weisberg, An Introduction to Regression Graphics. New York: Wiley, 1994.
• Fox, J. Regression Diagnostics: An Introduction. Newbury Park, CA.: Sage, 1991.
• Fox, J. Applied Regression Analysis, Linear Models, and Related Methods. Newbury Park, CA.: Sage, 1997,
• Mosteller, F., & Tukey, J. W. (1977). Data analysis and regression: A second course in statistics. Reading, MA: Addison-Wesley.
• Chatterjee, S. and Price, B. Regression Analysis by Example. Wiley, New York, 1977.

Tutorial and Technical Papers

• Conger, A. J., & Jackson, D. N. (1972). Suppressor variables, prediction, and the interpretation of psychological relationships. Educational and Psychological Measurement, 32, 579-599.
• Gocka, E. F. (1973). Stepwise regression for mixed mode predictor variables. Educational and Psychological Measurement, 33, 319-325.
• Cronbach, L. J. (1987). Statistical tests for moderator variables: Flaws in analyses recently proposed. Psychological Bulletin, 102, 414-417.
• Darlington, R. B. (1968). Multiple regression in psychological research and practice. Psychological Bulletin, 69, 161-182.
• Denby, L., & Pregibon, D. (1987). An example of the use of graphics in regression. The American Statistician, 41, 33-38.
• Dunlap, W. P., & Kemery, E. R. (1987). Failure to detect moderating effects: Is multicollinearity the problem? Psychological Bulletin, 102, 418-420.
• Flack, V. F., & Chang, P. C. (1987). Frequency of selecting noise variables in subset regression analysis: A simulation study. The American Statistician, 41, 84-86.
• Gorsuch, R. L. (1973). Data analysis of correlated independent variables. Multivariate Behavioral Research, 8, 89-107.
• Green, S. A. (1991). How many subjects does it take to do a multiple regression analysis? Multivariate Behavioral Research, 26, 499-510.
• James, L.R.and Brett, J.M. (1984). Mediators, Moderators, and Tests for Mediation, Journal of Applied Psychology, 69(2), pp. 307-321.
• Knoke, David, (1975). "A Comparison of Log-Linear and Regression Models for Systems of Dichotomous Variables," Sociological Methods and Research, 3 (May, 1975), 416-433.
• Lorenz, F. O. (1987). Teaching about influence in simple regression. Teaching Sociology, 15, 173-177.
• Mansfield, E. R., & Conerly, M. D. (1987). Diagnostic value of residual and partial residual plots. The American Statistician, 41, 107-116.
• McCabe, G. P., Jr. (1980). The interpretation of regression analysis results in sex and race discrimination problems. The American Statistician, 34, 212-215.
• Morris, J. H., Sherman, J. D., & Mansfield, E. R. (1986). Failures to detect moderating effects with ordinary least squares-moderated multiple regression: Some reasons and a remedy. Psychological Bulletin, 99, 282-288.
• Simon, G. A., & Simonoff, J. S. (1986). Diagnostic plots for missing data in least squares regression. Journal of the American Statistical Association, 81, 501-509.
• Spiegelman, C. H. (1986). Two pitfalls of using standard regression diagnostics when both X and Y have measurement error. The American Statistician, 40, 245-248.
• Stevens, J. P. (1984). Outliers and influential data points in regression analysis. Psychological Bulletin, 95, 334-344.
• Stone-Romero, E.F.and Anderson, L.E. (1994). Relative Power of Moderated Multiple Regression and the Comparison of Subgroup Correlation Coefficients for Detecting Moderating Effects, Journal of Applied Psychology, 79(3), pp. 354-359.
• Takane, Y., & Cramer, E. M. (1975). Regions of significance in multiple regression analysis. Multivariate Behavioral Research, 10, 373-383.
• Wolf, G., & Cartwright, B. (1974). Rules for coding dummy variables in multiple regression. Psychological Bulletin, 81, 173-179.
• Cohen, J. Partialed products are interactions: Partialed powers are curve components. Psychological Bulletin, 85:858-866, 1978.
• Cohen, A. Dummy variables in stepwise regression. The American Statistician, 45:226-228, 1991.
• Conger, A. J. A revised definition for suppressor variables: A guide to their identification and interpretation. Educational and Psychological Measurement, 34:35-46, 1974.
• Davison, M. L. and Sharma, A. R. Parametric statistics and levels of measurement: Factorial designs and multiple regression. Psychological Bulletin, 107:394-400, 1990.
• Evans, M. G. The problem of analyzing multiplicative composites: Interactions revisited. American Psychologist, 46:6-15, 1991.
• Foster, E. M. and McLanahan, S. An illustration of the use of instrumental variables: Do neighborhood conditions affect a young person's chance of finishing high school? Psychological Methods, 1(3):249-260, 1996.
• Franklin, L. A. Graphical insight into multiple regression concepts. The American Statistician, 46:284-288, 1992.
• Ganzach, Y. Misleading interaction and curvilinear terms. Psychological Methods, 2(3):235-247, 1997.
• Jaccard, J., Wan, C. K., and Turrisi, R. The detection and interpretation of interaction effects between continuous variables in multiple regression. Multivariate Behavioral Research, 25:467-478, 1990.
• Lubinski, D. and Humphreys, L. G. Assessing spurious ``moderator effects'': Illustrated substantively with the hypothesized (``synergistic'') relation between spatial and mathematical ability. Psychological Bulletin, 107:385-393, 1990.
• Mauro, R. Understanding l.o.v.e. (left out variables error): A method for estimating the effects of omitted variables. Psychological Bulletin, 108:314-329, 1990.
• O'Grady, K. E. and Medoff, D. R. Categorical variables in multiple regression: Some cautions. Multivariate Behavioral Research, 23:243-260, 1988.
• Paunonen, S. V. and Gardner, R. C. Biases resulting from the use of aggregated variables in psychology. Psychological Bulletin, 109:520-523, 1991.
• Tzelgov, J. and Henik, A. Suppression situations in psychological research: Definitions, implications, and applications. Psychological Bulletin, 109:524-536, 1991.

  Structural Equations and Path Analysis

• Biddle, B. J., & Marlin, M. M. (1987). Causality, confirmation, credulity, and structural equation modeling. Child Development, 58, 4-17.
• Connell, J. P., & Tanaka, J. S. (1987). Introduction to the special section on structural equation modeling. Child Development, 58, 2-3.
• Hatcher, L. (1994). A Step-by-Step Approach to using the SAS® System for Factor Analysis and Structural Equation Modeling. Cary, N.C.: SAS Institute.
• Martin, J. A. (1987). Structural equation modeling: A guide for the perplexed. Child Development, 58, 33-37.

  Logistic regression

• Fox, J. D. (1984). Linear Statistical Models and Related Methods. New York: Wiley.

  [Chapter 5 is an excellent introduction to logistic regression]

• Hosmer, D.W., & Lemeshow, S. (1989). Applied Logistic Regression. New York: Wiley.
• Walsh, A. Teaching understanding and interpretation of logit regression. Teaching Sociology, 15:178-183, 1987.
• Whitemore, A.S. (1981). "Sample size for logistic regression with small response probability" JASA, 76, 27-32.

  Research Applications

• Bailey, S. L., Flewelling, R. L., & Rachal, J. V. (1992). Predicting continued use of marijuana among adolescents: The relative influence of drug-specific and social context factors. Journal of Health and Social Behavior, 33, 51-66.
• Bhattacharyya, A. K. (1975). Income inequality and fertility: a compatative view. Population studies, 29, 5-18.
• Boster, J. S. (1988). Natural sources of internal category structure: typicality, familiarity and similarity of birds. Memory and Cognition, 16, 258-270.
• Capel, S. A. (1986). Psychological and organizational factors related to burnout in atheltic trainers. Research Quarterly for Exercise and Sport, 57, 321-328.
• Cohen, P. and Gaughran, E. An assessment of the impact of economic factors on planned fertility in New York City, 1970. Multivariate Behavioral Research, 11:461-476, 1976.
• Bradley, L. (1988). Making connections in learning to read and to spell. Applied Cognitive Psychology, 2, 3-18.
• Braune, R., & Wickens, C. D. (1986). Time-sharing revisted: test of a componential model for the assessment of individual differences. Ergonomics, 29, 1399-1414.
• Clark, D. A., & Beck, A. T. (1991). Personality factors in dysphoria: A psychometric refinement of Beck's Sociotropy-Autonomy scale. Journal of Psychopathology and Behavioral Assessment, 13, 369-.
• Clark, D. A., Beck, A. T., & Brown, G. T. (1992). Sociotropy, autonomy, and life event perception in dysphoric and nondysphoric individuals. Cognitive Therapy and Research, 16, 635-.
• Forehand, R. Fauber, R., Long, N., Brody, G. H. & Slotkin, J. (1987). Maternal depressive mood following divorce: An examination of predictors and adolescnt adjustment from a stress model perspective. Advances in Family Intervention, Assessment, and Therapy, Vol. 4, 71-.
• Frank, L. H., Casali, J. G., & Wierwille, W. W. (1988). Effects of visual display and motion system delays on operator performance and uneasiness in a driving simulator. Human Factors, 30(2), 201-217.
• Friedrich, W. N., Urquiza, A. J., & Beilke, R. L. (1986). Behavior problems in sexually abused young children. Journal of Pediatric Psychology, 11, 47-.
• Lovett, M. W., Benson, N. J., & Olds, J. (1990). Individual difference predictors of treatment outcome in the remediation of specific reading disability. Learning and Individual Differences, 2, 287-314.
• Marsh, H. W. (1987). Masculinity, Femininity and androgeny: Their relations with multiple dimensions of self-concept. Multivariate Behavioral Research, 22, 91-118.
• Rubin, D. C. (1980) 51 Properties of 125 words: A unit analysis of verbal behavior. Journal of Verbal Learning and Verbal Behavior, 19, 736-755.
• Tanaka, J. S. & Huba, G. J. (1987). Assessing the stability of depression in college students. Multivariate Behavioral Research, 22, 5-19.

© 1995 Michael Friendly