參考資料

Adair, G. (1984). The hawthorne effect: A reconsideration of the methodological artifact. Journal of Applied Psychology, 69, 334–345.

Agresti, A. (1996). An introduction to categorical data analysis. Wiley.

Agresti, A. (2002). Categorical data analysis (2nd ed.). Wiley.

Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716–723.

Anscombe, F. J. (1973). Graphs in statistical analysis. American Statistician, 27, 17–21.

Bickel, P. J., Hammel, E. A., & O’Connell, J. W. (1975). Sex bias in graduate admissions: Data from Berkeley. Science, 187, 398–404.

Box, G. E. P. (1953). Non-normality and tests on variances. Biometrika, 40, 318–335.

Box, J. F. (1987). Guinness, gosset, fisher, and small samples. Statistical Science, 2, 45–52.

Brown, M. B., & Forsythe, A. B. (1974). Robust tests for equality of variances. Journal of the American Statistical Association, 69, 364–367.

Campbell, D. T., & Stanley, J. C. (1963). Experimental and quasi-experimental designs for research. Houghton Mifflin.

Chronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334.

Cochran, W. G. (1954). The χ² test of goodness of fit. The Annals of Mathematical Statistics, 23, 315–345.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum.

Cramer, H. (1946). Mathematical methods of statistics. Princeton University Press.

Dunn, O. J. (1961). Multiple comparisons among means. Journal of the American Statistical Association, 56, 52–64.

Ellis, P. D. (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results. Cambridge University Press.

Evans, J. St. B. T., Barston, J. L., & Pollard, P. (1983). On the conflict between logic and belief in syllogistic reasoning. Memory and Cognition, 11, 295–306.

Evans, M., Hastings, N., & Peacock, B. (2011). Statistical distributions (3rd ed). Wiley.

Everitt, B. S. (1996). Making sense of statistics in psychology. A second-level course. Oxford University Press.

Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272–299.

Fisher, R. A. (1922a). On the interpretation of χ² from contingency tables, and the calculation of p. Journal of the Royal Statistical Society, 84, 87–94.

Fisher, R. A. (1922b). On the mathematical foundation of theoretical statistics. Philosophical Transactions of the Royal Society A, 222, 309–368.

Fisher, R. A. (1925). Statistical methods for research workers. Oliver & Boyd.

Fox, J., & Weisberg, S. (2011). An R companion to applied regression (2nd ed.). Sage.

Gelman, A., & Loken, E. (2014). The statistical crisis in science. American Scientist, 102(6), 460+. https://doi.org/10.1511/2014.111.460

Gelman, A., & Stern, H. (2006). The difference between “significant” and “not significant” is not itself statistically significant. The American Statistician, 60, 328–331.

Geschwind, N. (1972). Language and the brain. Scientific American, 226(4), 76–83.

Hays, W. L. (1994). Statistics (5th ed.). Harcourt Brace.

Hedges, L. V. (1981). Distribution theory for glass’s estimator of effect size and related estimators. Journal of Educational Statistics, 6, 107–128.

Hewitt, A. K., Foxcroft, D. R., & MacDonald, J. (2004). Multitrait-multimethod confirmatory factor analysis of the attributional style questionnaire. Personality and Individual Differences, 37(7), 1483–1491.

Hogg, R. V., McKean, J. V., & Craig, A. T. (2005). Introduction to mathematical statistics (6th ed.). Pearson.

Holm, S. (1979). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6, 65–70.

Hróbjartsson, A., & Gøtzsche, P. (2010). Placebo interventions for all clinical conditions. Cochrane Database of Systematic Reviews, 1. https://doi.org//10.1002/14651858.CD003974.pub3

Hsu, J. C. (1996). Multiple comparisons: Theory and methods. Chapman; Hall.

Ioannidis, J. P. A. (2005). Why most published research findings are false. PLoS Med, 2(8), 697–701.

Jeffreys, H. (1961). The theory of probability (3rd ed.). Oxford.

Johnson, V. E. (2013). Revised standards for statistical evidence. Proceedings of the National Academy of Sciences, 48, 19313–19317.

Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological Review, 80, 237–251.

Kass, R. E., & Raftery, A. E. (1995). Bayes factors. Journal of the American Statistical Association, 90, 773–795.

Keynes, J. M. (1923). A tract on monetary reform. Macmillan; Company.

Kruschke, J. K. (2011). Doing Bayesian data analysis: A tutorial with R and BUGS. Academic Press.

Kruskal, W. H., & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47, 583–621.

Kühberger, A., Fritz, A., & Scherndl, T. (2014). Publication bias in psychology: A diagnosis based on the correlation between effect size and sample size. Public Library of Science One, 9, 1–8.

Larntz, K. (1978). Small-sample comparisons of exact levels for chi-squared goodness-of-fit statistics. Journal of the American Statistical Association, 73, 253–263.

Lee, M. D., & Wagenmakers, E.-J. (2014). Bayesian cognitive modeling: A practical course. Cambridge University Press.

Lehmann, E. L. (2011). Fisher, Neyman, and the creation of classical statistics. Springer.

Levene, H. (1960). Robust tests for equality of variances. In I. O. et al (Ed.), Contributions to probability and statistics: Essays in honor of harold hotelling (pp. 278–292). Stanford University Press.

Meehl, P. H. (1967). Theory testing in psychology and physics: A methodological paradox. Philosophy of Science, 34, 103–115.

Pearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine, 50, 157–175.

Peterson, C., & Seligman, M. (1984). Causal explanations as a risk factor for depression: Theory and evidence. Psychological Review, 91, 347–374.

Pfungst, O. (1911). Clever hans (the horse of mr. Von osten): A contribution to experimental animal and human psychology (C. L. Rahn, Trans.). Henry Holt.

Rosenthal, R. (1966). Experimenter effects in behavioral research. Appleton.

Sahai, H., & Ageel, M. I. (2000). The analysis of variance: Fixed, random and mixed models. Birkhauser.

Shaffer, J. P. (1995). Multiple hypothesis testing. Annual Review of Psychology, 46, 561–584.

Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52, 591–611.

Sokal, R. R., & Rohlf, F. J. (1994). Biometry: The principles and practice of statistics in biological research (3rd ed.). Freeman.

Stevens, S. S. (1946). On the theory of scales of measurement. Science, 103, 677–680.

Stigler, S. M. (1986). The history of statistics. Harvard University Press.

Student, A. (1908). The probable error of a mean. Biometrika, 6, 1–2.

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124–1131.

Welch, B. L. (1947). The generalization of “Student’s” problem when several different population variances are involved. Biometrika, 34, 28–35.

Welch, B. L. (1951). On the comparison of several mean values: An alternative approach. Biometrika, 38, 330–336.

Wilkinson, L., Wills, D., Rope, D., Norton, A., & Dubbs, R. (2006). The grammar of graphics. Springer.