Statistical Methods for Psychology

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Vaughan, G. M., & Corballis, M. C. (1969). Beyond tests of
significance: Estimating strength of effects in selected
ANOVA designs. Psychological Bulletin, 72 , 204–223.
Venables, W. N. (2000). Exegeses on Linear Models. Paper
presented to the S-PLUS User’s Conference. Washington,
DC, 8–9th October, 1998. Available at http://www.stats
.ox.ac.uk/pub/MASS3/Exegeses.pdf.
Verdooren, L. R. (1963). Extended tables of critical values for
Wilcoxon’s test statistic. Biometrika, 50 , 177–186.
Vermont Department of Health. (1982). 1981 annual report of
vital statistics in Vermont. Burlington, VT.
Visintainer, M. A., Volpicelli, J. R., & Seligman, M. E. P.
(1982). Tumor rejection in rats after inescapable or escapable
shock. Science, 216 , 437–439.
Wagner, B. M., Compas, B. E., & Howell, D. C. (1988). Daily
and major life events: A test of an integrative model of psy-
chosocial stress. American Journal of Community Psychol-
ogy, 61 , 189–205.
Wainer, H. (1976). Estimating coefficients in linear models: It
don’t make no nevermind. Psychological Bulletin, 83 , 213–217.
Wainer, H. (1978). On the sensitivity of regression and regres-
sors. Psychological Bulletin, 85 , 267–273.
Wainer, H. (1984). How to display data badly. American Sta-
tistician, 38 , 137–147.
Watkins, A. E. (1995). The law of averages. Chance, 8 , 28–32.
Weaver, K. A. (1999). The statistically marvelous medical
growth chart: A tool for teaching variability. Teaching of
Psychology, 26 , 284–286.
Weinberg, C. R., & Gladen, B. C. (1986). The beta-geometric
distribution applied to comparative fecundability studies.
Biometrics, 42 , 547–560.
Weisberg, H. I. (1979). Statistical adjustments and uncon-
trolled studies. Psychological Bulletin, 86 , 1149–1164.
Welch, B. L. (1938). The significance of the difference between
two means when the population variances are unequal. Bio-
metrika, 29 , 350–362.
Welch, B. L. (1947). The generalization of Student’s problem
when several different population variances are involved.
Biometrika, 34 , 29–35.
Welch, B. L. (1951). On the comparison of several mean val-
ues: An alternative approach. Biometrika, 38 , 330–336.
Welkowitz, J., Ewen, R. B., & Cohen, J. (2000). Introductory
statistics for the behavioral sciences (5th ed.). New York:
Harcourt/Academic Press.
Welsch, R. E. (1977). Stepwise multiple comparison procedures.
Journal of the American Statistical Association, 72 , 566–575.
Werner, M., Stabenau, J. B., & Pollin, W. (1970). TAT meth-
ods for the differentiation of families of schizophrenics,
delinquents, and normals. Journal of Abnormal Psychology,
75 , 139–145.
Wickens, T. D. (1989). Multiway contingency table analysis
for the social sciences. Hillsdale, NJ: Erlbaum.


Wilcox, R. R. (1986). Critical values for the correlated t-test
when there are missing observations. Communications in
Statistics,Simulation and Computation, 15 , 709–714.
Wilcox, R. R. (1987a). New designs in analysis of variance.
Annual Review of Psychology, 38 , 29–60.
Wilcox, R. R. (1987b). New statistical procedures for the so-
cial sciences. Hillsdale, NJ: Erlbaum.
Wilcox, R. R. (1992). Why can methods for comparing means
have relatively low power, and what can you do to correct
the problem? Current Directions in Psychological
Science, 1 , 101–105.
Wilcox, R. R. (1993). Analyzing repeated measures or ran-
domized block designs using trimmed means. British
Journal of Mathematical and Statistical Psychology, 46 ,
63–76.
Wilcox, R. R. (1995). ANOVA: The practical importance of
heteroscedastic methods, using trimmed means versus
means, and designing simulation studies. British Journal of
Mathematical and Statistical Psychology, 48 ,99–114.
Wilcox, R. R. (2005). Trimmed means. In Everitt, B. E. &
Howell, D. C. Encyclopedia of statistics in behavioral sci-
ence. Chichester, England: Wiley.
Williams, E. J. (1959). The comparison of regression vari-
ables. Journal of the Royal Statistical Society (Series B), 21 ,
396–399.
Wilkinson, L. (1994). Less is more: Two- and three- dimen-
sional graphics for data display. Behavior Research Meth-
ods,Instrumentation,and Computers, 26 , 172–176.
Wilkinson, L. (1999). Statistical methods in psychology jour-
nals: Guidelines and explanations. American Psychologist.
54 , 594–604.
Winer, B. J. (1962). Statistical principles in experimental
design. New York: McGraw-Hill.
Winer, B. J. (1971). Statistical principles in experimental
design(2nd ed.). New York: McGraw-Hill.
Winer, B. J., Brown, D. R., & Michels, K. M. (1991). Statisti-
cal Principles in Experimental Design (3rd ed.). New York:
McGraw-Hill.
Yates, F. (1934). Contingency tables involving small numbers
and the test. Supplement. Journal of the Royal Statistical
Society (Series B), 1 , 217–235.
Yuen, K. K., & Dixon, W. J. (1973). The approximate behav-
ior and performance of the two-sample trimmed t. Bio-
metrika, 60 , 369–374.
Zuckerman, M., Hodgins, H. S., Zuckerman, A., & Rosenthal,
R. (1993). Contemporary issues in the analysis of data. Psy-
chological Science, 4 , 49–53.
Zumbo, B. D., & Zimmerman, D. W. (2000). Scales of
measurement and the relation between parametric and
nonparametric statistical tests. In Thompson, B. (Ed.), Ad-
vances in social science methodology,Vol. 6. Greenwich,
CT: JAI Press.

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