Recommended Statistics References for Simple and Multiple Regression
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Achen, C. H. (1982). Interpreting and using regression. Beverly Hills, CA: Sage.

Achen, C. H. (1982). Interpreting and using regression. Series: Quantitative Applications in the Social Sciences, No. 29. Thousand Oaks, CA: Sage Publications.

Allen, D.M. (1971), "Mean Square Error of Prediction as a Criterion for Selecting Variables," Technometrics, 13, 469 -475.

Allen, D.M. and Cady, F.B. (1982), Analyzing Experimental Data by Regression, Belmont, CA: Lifetime Learning Publications.

Allison, P. D. (1999). Multiple regression. Thousand Oaks, CA: Pine Forge Press.

Belsley, D.A., Kuh, E., and Welsch, R.E. (1980), Regression Diagnostics, New York: John Wiley & Sons, Inc.

Berk, R. A. (2004). Regression analysis: A constructive critique. Newbury Park, CA: Sage Publications.

Berry, W. D. (1993). Understanding Regression Assumptions. Series: Quantitative Applications in the Social Sciences, No. 92. Newbury Park, CA: Sage Publications.

Bock, R.D. (1975), Multivariate Statistical Methods in Behavioral Research, New York: McGraw-Hill Book Co.

Box, G.E.P. (1966), "The Use and Abuse of Regression," Technometrics, 8, 625 -629.

Breen, R. (1996). Regression Models: Censored, Sample Selected or Truncated Data, by

Chatterjee, S. and Price, B. Regression Analysis by Example. Wiley, New York, 1977.

Chatterjee, S., Hadi, A., & Price, B. (2000) Regression analysis by example. New York: Wiley. ISBN 0-471-31946-5

Cody, R., & Pass, R. (1995). SAS Programming by example. Cary, NC: SAS Institute, Inc.

Cohen, A. Dummy variables in stepwise regression. The American Statistician, 45:226-228, 1991.

Cohen, J. (1990). Things I have learned (so far). American Psychologist, 45, 1304-1312.

Cohen, J. (2003). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. (3 rd ed.). Lawrence Erlbaum Associates.

Cohen, J. Partialed products are interactions: Partialed powers are curve components. Psychological Bulletin, 85:858-866, 1978.

Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.

Cohen, J., and Cohen, P. (1975). Applied Multiple Regression and Correlation Analysis for the Behavioral Sciences, Hillsdale, New Jersey: Lawrence Erlbaum Associates.

Conger, A. J., & Jackson, D. N. (1972). Suppressor variables, prediction, and the interpretation of psychological relationships. Educational and Psychological Measurement, 32, 579-599.

Conger, A. J. A revised definition for suppressor variables: A guide to their identification and interpretation. Educational and Psychological Measurement, 34:35-46, 1974.

Cook, R.D. (1977), "Detection of Influential Observations in Linear Regression," Technometrics, 19, 15 -18.

Cook, R.D. (1979), "Influential Observations in Linear Regression," Journal of the American Statistical Association, 74, 169 -174.

Cronbach, L. J. (1987). Statistical tests for moderator variables: Flaws in analyses recently proposed. Psychological Bulletin, 102, 414-417.

Cronbach, L. J., & Gleser, G.C. (1965). Psychological tests and personnel decisions (2nd ed.). Urbana: University of Illinois Press.

Daniel, C. and Wood, F. (1980), Fitting Equations to Data, Revised Edition, New York: John Wiley & Sons, Inc.

Darlington, R. B. (1968). Multiple regression in psychological research and practice. Psychological Bulletin, 69, 161-182.

Darlington, R.B. (1968), "Multiple Regression in Psychological Research and Practice," Psychological Bulletin, 69, 161 -182.

Davison, M. L. and Sharma, A. R. Parametric statistics and levels of measurement: Factorial designs and multiple regression. Psychological Bulletin, 107:394-400, 1990.

Dawes, R. M., Faust, D., & Meehl, P. E. (1989). Clinical versus actuarial judgment. Scienc, 243 1668-1674.

Denby, L., & Pregibon, D. (1987). An example of the use of graphics in regression. The American Statistician, 41, 33-38.

Draper, N. and Smith, H. (1981), Applied Regression Analysis, Second Edition, New York: John Wiley & Sons, Inc.

Dunlap, W. P., & Kemery, E. R. (1987). Failure to detect moderating effects: Is multicollinearity the problem? Psychological Bulletin, 102, 418-420.

Durbin, J. and Watson, G.S. (1951), "Testing for Serial Correlation in Least Squares Regression," Biometrika, 37, 409 -428.

Evans, M. G. The problem of analyzing multiplicative composites: Interactions revisited. American Psychologist, 46:6-15, 1991.

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.

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.

Fowler, R. L. (1986). Confidence intervals for the cross-validated multiple correlation in predictive regression models, Journal of Applied Psychology, 71, 318-322.

Fox, J. (1991). Regression Diagnostics. Newbury Park, CA: Sage Publications. Quantitative Applications in the Social Sciences Series No. 79.

Fox, J. (1997) Applied regression analysis, linear models, and related methods. Thousand Oaks, CA: Sage Publications. ISBN 0-8039-4540-X

Fox, J. (2000). Nonparametric simple regression: Smoothing scatter plots. Thousand Oaks, CA: Sage Publications. Quantitative Applications in the Social Sciences Series No.130.

Franklin, L. A. Graphical insight into multiple regression concepts. The American Statistician, 46:284-288, 1992.

Freund, R.J. and Littell, R.C. (1986), SAS System for Regression, 1986 Edition, Cary, NC: SAS Institute Inc.

Freund, R.J., Littell, R.C., and Spector P.C. (1991), SAS System for Linear Models, Cary, NC: SAS Institute Inc.

Ganzach, Y. Misleading interaction and curvilinear terms. Psychological Methods, 2(3):235-247, 1997.

Gocka, E. F. (1973). Stepwise regression for mixed mode predictor variables. Educational and Psychological Measurement, 33, 319-325.

Gonick, L., & Smith, W. (1993). The cartoon guide to statistics. New York: Harper Perennial.

Goodnight, J.H. (1979), "A Tutorial on the SWEEP Operator," The American Statistician, 33, 149-158. (Also available as SAS Technical Report R-106, The Sweep Operator: Its Importance in Statistical Computing, Cary, NC: SAS Institute Inc.)

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.

Grimm, L.G., & Yarnold, P.R. (1995). Reading and understanding multivariate statistics. Washington, DC: American Psychological Association.

Grimm, L.G., & Yarnold, P.R. (2000). Reading and understanding more multivariate statistics. Washington, DC: American Psychological Association.

Hamilton, L.C. (1992) Regression with graphics. Belmont, CA: Wadsworth. ISBN 0-534-15900-1

Hawkins, D.M. (1980), "A Note on Fitting a Regression With No Intercept Term," The American Statistician, 34, 233.

Hays, W. L. (1988). Statistics (4th ed.). Chicago: Holt, Rinehart & Winston. 

Hosmer, D.W., & Lemeshow, S. (1989). Applied logistic regression. New York: John Wiley & Sons.

Jaccard, J. (2003). Interaction effects in multiple regression. Thousand Oaks, CA: Sage Publications. Series: Quantitative Applications in the Social Sciences, No. 72.

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.

James, L.R. and Brett, J.M. (1984). Mediators, Moderators, and Tests for Mediation, Journal of Applied Psychology, 69(2), pp. 307-321.

Johnston, J. (1972), Econometric Methods, New York: McGraw-Hill Book Co.

Kahane, L. H. (2001). Regression basics. Thousand Oaks, CA: Sage Publications.

Kazdin, A.E. (1998). Methodological issues and strategies in clinical research (2nd ed.). Washington, DC: American Psychological Association.

Kennedy, W.J. and Gentle, J.E. (1980), Statistical Computing, New York: Marcel Dekker, Inc.

Kerlinger, F. N. (1986). Foundation of behavioral research (3rd ed. ). New York: Holt, Rinehart & Winston.

Kvalseth, T.O. (1985), "Cautionary Note About R2," The American Statistician, 39, 279.

Lewis-Beck, M.S. (1980). Applied regression: An introduction, Beverly Hills, CA: Sage.

Linn, R. L. (Ed.). (1989). Educational measurement (3rd ed.). London: Cassel & Collier Macmillian.

Lorenz, F. O. (1987). Teaching about influence in simple regression. Teaching Sociology, 15, 173-177.

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.

Mallows, C.L. (1973), "Some Comments on Cp," Technometrics, 15, 661 -75.

Mansfield, E. R., & Conerly, M. D. (1987). Diagnostic value of residual and partial residual plots. The American Statistician, 41, 107-116.

Mardia, K.V., Kent, J.T., and Bibby, J.M. (1979), Multivariate Analysis, London: Academic Press.

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.

McCabe, G. P., Jr. (1980). The interpretation of regression analysis results in sex and race discrimination problems. The American Statistician, 34, 212-215.

Menard, S. (2002). Applied logistic regression analysis. Thousand Oaks, CA: Sage Publications. Series: Quantitative Applications in the Social Sciences, No. 106.

Miles, J. (2001). Applying regression and correlation: A guide for students and Reseachers. Beverly Hills , CA: Sage Publications.

Mitchell, T. W., & Klimoski, R. J. (1986). Estimating the validity of cross-validity estimation. Journal of Applied Psychology., 71, 311-317.

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.

Morrison, D.F. (1976), Multivariate Statistical Methods, Second Edition, New York: McGraw-Hill Book Co.

Mosteller, F. and Tukey, J.W. (1977), Data Analysis and Regression, Reading, MA: Addison-Wesley Publishing Co., Inc.

Mosteller, F., & Tukey, J. W. (1977). Data analysis and regression: A second course in statistics. Reading, MA: Addison-Wesley.

Murphy (1997), The American Statistician, 51(2), 155-157 for ``How to read the statistical methods literature: A guide for students''.

Neter, J. and Wasserman, W. (1974), Applied Linear Statistical Models, Homewood, IL: Irwin.

Nicol, A.A.M., & Pexman, P.M. (1999). Presenting your findings: A practical guide for creating tables. Washington, DC: American Psychological Association.

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.

Pedhazur, E. J. (1982). Multiple regression in behavioral research: Explanation and prediction (2nd ed.). New York: Holt, Rinehart & Winston.

Pedhazur, E. J. Multiple regression in behavioral research: explanation and prediction (3 rd ed). Harcourt Brace College Publishers.

Pedhazur, E.J. (1997). Multiple regression in behavioral research, third edition. New York: Harcourt Brace College Publishers. ISBN 0-03-072831-2

Pillai, K.C.S. (1960), Statistical Table for Tests of Multivariate Hypotheses, Manila: The Statistical Center, University of Philippines.

Pindyck, R.S. and Rubinfeld, D.L. (1981), Econometric Models and Econometric Forecasts, Second Edition, New York: McGraw-Hill Book Co.

Rao, C.R. (1973), Linear Statistical Inference and Its Applications, Second Edition, New York: John Wiley & Sons, Inc.

Rawlings, J.O. (1988), Applied Regression Analysis: A Research Tool, Pacific Grove, California: Wadsworth & Brooks/Cole Advanced Books & Software.

Richard Breen. Quantitative Applications in the Social Sciences Series, No. 111. Thousand Oaks, CA: Sage Publications.

Schroeder, L. D. (1986). Understanding regression analysis: An introductory guide. Beverly Hills, CA: Sage Publications. No. 57.

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.

Spector, P.E. (1999). SAS programming for researchers and social scientists. Newbury Park: Sage Publications.

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.

Steinberg, L. Elmen, J.D. & Mounts, N.S. (1989). Authoritative parenting, psychosocial maturity and academic success among adolescents. Child Development, 60, 1424-1436.

Stevens, J. (1999). Applied multivariate statistics for the social sciences (3th Ed.). Hillsdale, NJ: Lawrence Erlbuam Associates

Stevens, J. (1999). Intermediate statistics: A modern approach (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.

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.

Tabachnick, B. G. and L.S. Fidell (2001). Using Multivariate Statistics, 4th Ed. Boston: Allyn and Bacon

Takane, Y., & Cramer, E. M. (1975). Regions of significance in multiple regression analysis. Multivariate Behavioral Research, 10, 373-383.

Tatsuoka, M. M. (1975). The general linear model: A new trend in analysis of variance. Champaign, Il.: Institute for Personality and Ability Testing.

Timm, N.H. (1975), Multivariate Analysis with Applications in Education and Psychology, Monterey, CA: Brooks-Cole Publishing Co.

Tzelgov, J. and Henik, A. Suppression situations in psychological research: Definitions, implications, and applications. Psychological Bulletin, 109:524-536, 1991.

Weisberg, S. (1985), Applied Linear Regression, Second Edition. New York: John Wiley & Sons, Inc.

Wiggins, J.S. (1973). Personality and prediction: Principles of personality assessment. Reading, MA: Addison-Wesley.

Willshire, D., Kinsella, G., & Prior, M. (1991). Estimating WAIS-R IQ from the National Adult Reading Test: A cross-validation. Journal of Clinical and Experimental Neuropsychology, 13, 204-216.

Wolf, G., & Cartwright, B. (1974). Rules for coding dummy variables in multiple regression. Psychological Bulletin, 81, 173-179.

Younger, M.S. (1979), Handbook for Linear Regression, North Scituate, MA: Duxbury Press.

 

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