Regression References
Multivariate Data Analysis
Psychology 6140
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: AddisonWesley.
 Chatterjee, S. and Price, B.
Regression Analysis by Example.
Wiley, New York, 1977.
See Murphy (1997), The American Statistician, 51(2), 155157
for ``How to read the statistical methods literature: A guide for students''.
 Conger, A. J., & Jackson, D. N. (1972). Suppressor variables, prediction, and the
interpretation of psychological relationships. Educational and Psychological Measurement,
32, 579599.
 Gocka, E. F. (1973). Stepwise regression for mixed mode predictor variables. Educational
and Psychological Measurement, 33, 319325.
 Cronbach, L. J. (1987). Statistical
tests for moderator variables: Flaws in analyses recently
proposed. Psychological Bulletin, 102, 414417.
 Darlington, R. B. (1968). Multiple
regression in psychological research and practice.
Psychological Bulletin, 69, 161182.
 Denby, L., &
Pregibon, D. (1987). An example of the use of graphics
in regression. The American Statistician, 41, 3338.
 Dunlap, W. P., & Kemery, E. R. (1987).
Failure to detect moderating effects: Is multicollinearity
the problem? Psychological Bulletin, 102, 418420.
 Flack, V. F., &
Chang, P. C. (1987). Frequency of selecting noise
variables in subset regression analysis: A simulation study.
The American Statistician, 41, 8486.
 Gorsuch, R. L. (1973).
Data analysis of correlated independent variables.
Multivariate Behavioral Research, 8, 89107.
 Green, S. A. (1991). How
many subjects does it take to do a multiple regression
analysis? Multivariate Behavioral Research, 26, 499510.
 James, L.R.and Brett, J.M. (1984). Mediators, Moderators, and Tests
for Mediation, Journal of Applied Psychology, 69(2), pp.
307321.
 Knoke, David, (1975). "A Comparison of LogLinear and Regression Models for Systems of Dichotomous Variables," Sociological Methods and Research, 3 (May, 1975), 416433.
 Lorenz, F. O.
(1987). Teaching about influence in simple regression.
Teaching Sociology, 15, 173177.
 Mansfield, E.
R., & Conerly, M. D. (1987). Diagnostic value of
residual and partial residual plots. The American
Statistician, 41, 107116.
 McCabe, G. P., Jr.
(1980). The interpretation of regression analysis
results in sex and race discrimination problems. The
American Statistician, 34, 212215.
 Morris, J. H., Sherman, J. D., & Mansfield,
E. R. (1986). Failures to detect moderating effects with
ordinary least squaresmoderated multiple regression: Some
reasons and a remedy. Psychological Bulletin, 99, 282288.
 Simon, G. A., &
Simonoff, J. S. (1986). Diagnostic plots for missing
data in least squares regression. Journal of the
American Statistical Association, 81, 501509.
 Spiegelman, C. H. (1986). Two
pitfalls of using standard regression diagnostics when both
X and Y have measurement error. The
American Statistician, 40, 245248.
 Stevens, J. P.
(1984). Outliers and influential data points in
regression analysis. Psychological Bulletin, 95, 334344.
 StoneRomero, 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. 354359.
 Takane, Y., & Cramer, E. M.
(1975). Regions of significance in multiple regression
analysis. Multivariate Behavioral Research, 10, 373383.
 Wolf, G., & Cartwright, B.
(1974). Rules for coding dummy variables in multiple
regression. Psychological Bulletin, 81, 173179.
 Cohen, J.
Partialed products are interactions: Partialed powers are curve
components.
Psychological Bulletin, 85:858866, 1978.
 Cohen, A.
Dummy variables in stepwise regression.
The American Statistician, 45:226228, 1991.
 Conger, A. J.
A revised definition for suppressor variables: A guide to their identification
and interpretation.
Educational and Psychological Measurement, 34:3546, 1974.
 Davison, M. L.
and Sharma, A. R.
Parametric statistics and levels of measurement: Factorial designs and multiple
regression.
Psychological Bulletin, 107:394400, 1990.
 Evans, M. G.
The problem of analyzing multiplicative composites: Interactions revisited.
American Psychologist, 46:615, 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):249260, 1996.
 Franklin, L. A.
Graphical insight into multiple regression concepts.
The American Statistician, 46:284288, 1992.
 Ganzach, Y.
Misleading interaction and curvilinear terms.
Psychological Methods, 2(3):235247, 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, 25:467478, 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, 107:385393, 1990.
 Mauro, R.
Understanding l.o.v.e. (left out variables error): A method for estimating the
effects of omitted variables.
Psychological Bulletin, 108:314329, 1990.
 O'Grady, K. E.
and Medoff, D. R.
Categorical variables in multiple regression: Some cautions.
Multivariate Behavioral Research, 23:243260, 1988.
 Paunonen,
S. V. and Gardner, R. C.
Biases resulting from the use of aggregated variables in psychology.
Psychological Bulletin, 109:520523, 1991.
 Tzelgov, J. and
Henik, A.
Suppression situations in psychological research: Definitions, implications,
and applications.
Psychological Bulletin, 109:524536, 1991.
 Biddle, B.
J., & Marlin, M. M. (1987). Causality, confirmation,
credulity, and structural equation modeling. Child
Development, 58, 417.
 Connell, J.
P., & Tanaka, J. S. (1987). Introduction to the special
section on structural equation modeling. Child
Development, 58, 23.
 Hatcher, L. (1994).
A StepbyStep 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, 3337.
 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, 15:178183, 1987.

Whitemore, A.S.
(1981). "Sample size for logistic regression with small response
probability" JASA, 76, 2732.
 Bailey, S. L., Flewelling,
R. L., & Rachal, J. V. (1992). Predicting continued use
of marijuana among adolescents: The relative influence of
drugspecific and social context factors. Journal of
Health and Social Behavior, 33, 5166.
 Bhattacharyya, A. K.
(1975). Income inequality and fertility: a compatative
view. Population studies, 29, 518.
 Boster, J. S. (1988).
Natural sources of internal category structure: typicality,
familiarity and similarity of birds. Memory and
Cognition, 16, 258270.
 Capel, S. A. (1986). Psychological and
organizational factors related to burnout in atheltic
trainers. Research Quarterly for Exercise and
Sport, 57, 321328.
 Cohen, P. and
Gaughran, E.
An assessment of the impact of economic factors on planned fertility in New
York City, 1970.
Multivariate Behavioral Research, 11:461476, 1976.
 Bradley, L. (1988).
Making connections in learning to read and to spell.
Applied Cognitive Psychology, 2, 318.
 Braune, R., & Wickens, C. D.
(1986). Timesharing revisted: test of a componential
model for the assessment of individual differences.
Ergonomics, 29, 13991414.
 Clark, D. A., & Beck, A. T.
(1991). Personality factors in dysphoria: A psychometric
refinement of Beck's SociotropyAutonomy 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), 201217.
 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,
287314.
 Marsh, H. W. (1987).
Masculinity, Femininity and androgeny: Their relations with
multiple dimensions of selfconcept. Multivariate
Behavioral Research, 22, 91118.
 Rubin, D. C. (1980) 51
Properties of 125 words: A unit analysis of verbal behavior.
Journal of Verbal Learning and Verbal Behavior, 19,
736755.
 Tanaka, J. S. & Huba, G. J. (1987).
Assessing the stability of depression in college students.
Multivariate Behavioral Research, 22, 519.
© 1995 Michael Friendly
Author:
Michael Friendly
to PSY6140 info.