EXACT-STATS BIBLIOGRAPHY PART A: CONCEPTS AND DESIGNS 1-SEP-96, Compiled by Patrick Onghena, Katholieke Universiteit Leuven (Belgium), based on the advice from subscribers to the EXACT-STATS list. The current version of this part of the bibliography can be obtained by sending the following 1-line (no headers or footers) e-mail message : to: mailbase@mailbase.ac.uk message: send exact-stats bibliogen.txt You can also access this file, and other exact-stats files, via World Wide Web or via anonymous FTP. The URL is: http://www.mailbase.ac.uk/lists-a-e/exact-stats/files/bibliogen.txt The FTP site is ftp.mailbase.ac.uk Send questions, advice, or corrections to Patrick Onghena directly: Patrick.Onghena@ped.kuleuven.ac.be =========================================================================== The exact-stats bibliography is organised in four sections and corresponding files. The first section is in the file BIBLIOGEN.TXT and contains the core references on concepts and designs, the second section is in the file BIBLIOALG.TXT and contains references to algorithms, software announcements and software reviews, the third section is in the file BIBLIOPRE.TXT and contains references to preprints and recent publications (1994-1996), and the last section is in the file BIBLIOCOM.TXT and contains a comprehensive listing of publications on exact tests and related topics. The sections A and C are subdivided in books versus articles. A. CONCEPTS AND DESIGNS A1. BOOKS A2. ARTICLES B. ALGORITHMS C. PREPRINTS AND RECENT PUBLICATIONS C1. BOOKS C2. ARTICLES D. COMPREHENSIVE LISTING [Some references are followed by a code between square brackets giving the main characteristics and technical level of the text, using the following key:] Main characteristics A = good Advocacy I = accessible Introduction R = serves as a Reference work E = useful Examples S = link to accessible usable Software Technical Level T0 = Little statistical training required T1 = Undergraduate statistics T2 = Graduate statistics T3 = Advanced, current research {Annotations and keywords are given between braces} =========================================================================== A1. BOOKS Bradley, J. V. (1968). _Distribution-free statistical tests_. Englewood Cliffs, NJ: Prentice-Hall. Conover, W. J. (1980). _Practical nonparametric statistics_ (2nd ed.). New York: Wiley. {First edition 1971} Edgington, E. S. (1969). _Statistical inference: The distribution-free approach_. New York: McGraw-Hill. [AIRET0] Edgington, E. S. (1995). _Randomization tests_ (3rd ed.). New York: Marcel Dekker. [AIRET0]. {Previous editions 1980 and 1987; this edition includes two new chapters, Chapter 13 "Tests of quantitative laws", and Chapter 14 "Tests of direction and magnitude of effect", and an appendix written by Rose D. Baker on "Modern permutation test software" which includes RANDIBM, StatXact, SIMSTAT, SC, TESTIMATE, SAS, and SCRT.} Efron, B (1982). The jacknife, the bootstrap and other resampling plans. _CBMS-NSF Regional Conference Series in Applied Mathematics, Vol. 38_. Society for Industrial and Applied Mathematics. Efron, B., & Tibshirani, R. J. (1993). _An introduction to the bootstrap_. New York: Chapman & Hall. [AIRET123] Fisher, R. A. (1966). _The design of experiments_ (8th ed.). Edinburgh: Oliver & Boyd. (Original work published 1935). Good, P. (1994). _Permutation tests: A practical guide to resampling methods for testing hypotheses_. New York: Springer-Verlag. [AIET123] {Generally regarded as the most comprehensive and up-to-date general account of randomisation tests; the style is accessible; includes copious bibliographies} Hall, P. (1992). _The bootstrap and Edgeworth expansion_. New York: Springer-Verlag. Hinkelmann, K., & Kempthorne, O. (1994). _Design and analysis of experiments, Vol. 1: Introduction to experimental design_. New York: Wiley. [RT2] {An update of Kempthorne's 1952 classic. SAS is used to perform illustrative analyses, but only parametric statistical tests are used to approximate the randomization test. The second volume is in preparation and will deal with more technical aspects of the designs discussed in Volume I at the T3 level, and introduce some other designs.} Hubert, L. J. (1987). _Assignment methods in combinatorial data analysis_. New York: Marcel Dekker. Kempthorne, O. (1952). _Design and analysis of experiments_. New York: Wiley. [RT23] {The first textbook to elaborate on the Fisherian idea of a randomization test. Randomization theory is used merely to examine the validity of normal theory tests, not for their own sake.} Krauth, J. (1988). _Distribution-free statistics: An application oriented approach_. Amsterdam: Elsevier. {Links to the DISFREE software package, distributed by Biosoft, Cambridge, UK} Lehmann, E. (1975). _Nonparametrics: Statistical methods based on ranks_. San Francisco: Holden-Day. [R] {A classic work - one of the few from the older generation to cover both continuous and categorical data in a nonparametric setting. It does not tie the methods to any software (there was no software at that time)}. LePage, R. & Billard, L. (Eds.) (1992). _Exploring the limits of bootstrap_. New York: Wiley. Manly, B. F. J. (1991). _Randomization and Monte Carlo methods in biology_. London: Chapman & Hall. [AIEST0]. {Links to the 'RT' software package produced and marketed by Bryan Manly Associates} Maritz, J. S. (1995). _Distribution free statistical methods_ (2nd ed.). London: Chapman & Hall. {focuses on permutation methods and estimation techniques in nonparametrics, first edition 1981} May, R. B., Masson, M. E. J., & Hunter, M. A. (1990). _Application of statistics in behavioral research_. New York: Harper & Row. [AIEST0]. {An introductory statistics textbook that introduces hypothesis testing by means of the randomization test and the random assignment model. It is linked to the NPSTAT software package distributed by Richard B. May} Neyman, J. (1950). _First course in probability and statistics_. New York, NY: Holt. {contains classical follow-up discussion of Fisher's Lady Tasting Tea, pp. 272-294} Noreen, E. (1989). _Computer-intensive methods for testing hypotheses_. New York: Wiley. [AIST0] Siegel, S. (1956). _Nonparametric statistics for the behavioral sciences_. New York: McGraw-Hill. [IET0] {Chapters 5 and 6, Selector Table inside front cover also inside back cover.} Siegel, S., & Castellan, N. J., Jr. (1988). _Nonparametric statistics for the behavioral sciences_ (2nd ed.). New York: McGraw-Hill. [IET0] {Chapters 5 and 6, Selector Table inside back cover.} Simon, J. L. (1969). _Basic research methods in social science_. New York: Random House. {Contains the first publication of the Bootstrap, although not named as such} Simon, J. L. & Burstein, P. (1985). _Basic research methods in social science_ (3rd Ed.). New York: Random House. Simon, J. L. (1993). _Resampling: The new statistics_. Duxbury. [IT0] {An introduction to statistics from a resampling perspective, available through Resampling Stats, Inc., resample@cais.com}. Sprent, P. (1993). _Applied nonparametric statistical methods_ (2nd ed.). Chapman & Hall. [E] Westfall, P H. & Young, S. S. (1993). _Resampling-based multiple testing: Examples and methods for p-value adjustment_. New York: Wiley. [AEST23] {This book discusses multiple comparisons and the general multiple testing problem from the resampling perspective (both bootstrap and permutation methods are presented). Interesting examples using SAS MULTTEST, SAS IML, GAUSS, and RESAMPLING STATS are provided.} A2. ARTICLES Agresti, A. (1992). A survey of exact inference for contingency tables (with discussion). _Statistical Science, 7_, 131-172. [AIRES] Agresti, A., Wackerly, D., & Boyett, J. M. (1979). Exact conditional tests for cross-classifications: approximations of attained significance levels. _Psychometrika, 44_, 75-83. Albers, W., Bickel, P. J., & Van Zwet, W. R. (1976). Asymptotic expansions for the power of distribution-free tests in the one-sample problem. _The Annals of Statistics, 4_, 108-156. Arnold, H. J. (1964). Permutation support for multivariate techniques. _Biometrika, 51_, 65-70. Baker, F. B., & Collier, R. O. (1961). Analysis of experimental designs by means of randomization: A Univac 1103 program. _Behavioral Science, 6_, 369. Barnard, G. A. (1989). On alleged gains in power from lower p-values. _Statistics in Medicine, 8_, 1469-1477. Barnard, G. A. (1990). Must clinical trials be large? The interpretation of p-values and the combination of test results. _Statistics in Medicine, 9_, 601-614. [R] {This article by G. A. Barnard (together with the 1989 paper in Statistics in Medicine) offers strong advocacy for the 'Mid-P' procedure in exact significance testing} Barton, D. E., & David, F. N. (1961). Randomization basis for multivariate tests. _Bulletin of the International Statistical Institute, 39_, 455-467. Basu, D. (1980). Randomization analysis of experimental data: The Fisher randomization test. _Journal of the American Statistical Association, 75_, 575-582. Box, G. E. P., & Anderson, S. L. (1955). Permutation theory in the development of robust criteria and the study of departures from assumptions (with discussion). _Journal of the Royal Statistical Society Series B, 17_, 1-34. Boyett, J. M., & Shuster, J. J. (1977). Nonparametric one-sided tests in multivariate analysis with medical applications. _Journal of the American Statistical Association, 72_, 665-668. Bross, I. D. J. (1964). Taking a covariable into account. _Journal of the American Statistical Association, 59_, 725-736. Cox, D. R. (1956). A note on weighted randomization. _Annals of Mathematical Statistics, 27_, 1144-1150. Diaconis, P., & Efron, B. (1983). Computer-intensive methods in statistics. _Scientific American, 247(5)_, 96-129. [IET0] {account of the Bootstrap} Draper, D., Hodges, J. S., Mallows, C. L., & Pregibon, D. (1993). Exchangeability and data analysis (with discussion). _Journal of the Royal Statistical Society Series A, 156_, 9-37. {gives a definition of exchangeability; extends de Finetti's concept; examples in description, inference, and prediction; clarification of the extent to which judgments of exchangeability can be based on data, and the extent to which they must rely on pure faith; contains interesting discussion by Chatfield, Lindley, Ehrenberg and Bound, Barnard, Nelder, Consonni, Ellis, Forcina, Giudici, Godambe, Hartigan, and Rosenbaum} Dwass, M. (1957). Modified randomization tests for non-parametric hypotheses. _Annals of Mathematical Statistics, 28_, 181-187. Edgington, E. S. (1966). Statistical inference and nonrandom samples. _Psychological Bulletin, 66_, 485-487. Fisher, R. A. (1936). Coefficient of racial likeness and the future of craniometry. _Journal of the Royal Anthropological Society, 66_, 57-63. Freeman, G. H., & Halton, J. H. (1951). Note on an exact treatment of contingency, goodness-of-fit, and other problems of significance. _Biometrika, 38_, 141-149. {first publication on an exact test for r x c contingency tables} Gart, J. (1970). Point and interval estimation of the common odds ratio in the combination of 2x2 tables with fixed marginals. _Biometrika, 57_, 471-475. Gabriel, K. R., & Hsu, C. F. (1983). Evaluation of the power of rerandomization tests, with application to weather modification experiments. _Journal of the American Statistical Association, 78_, 766-775. Good, P. I. (1992). Globally almost powerful tests for censored data. _Nonparametric Statistics, 1_, 253-262. Goodman, L. A. (1979). Simple models for the analysis of association in cross-classifications having ordered categories. _Journal of the American Statistical Association, 74_, 537-552. Gridgeman, N. T. (1959). The lady tasting tea, and allied topics. _Journal of the American Statistical Association, 54_, 776-783. {contains classical follow-up discussion of Fisher's Lady Tasting Tea} Hoeffding, W. (1951). Combinatorial central limit theorem. _Annals of Mathematical Statistics, 22_, 556-558. Kempthorne, O., & Doerfler, T. E. (1969). The behaviour of some significance tests under experimental randomization. _Biometrika, 56_, 231-247. Lancaster, H. O. (1961). Significance tests in discrete distributions. _Journal of the American Statistical Association, 56_, 223-234. [R] {Introduces the 'Mid-P' procedure} Lehmann, E. L., & Stein, C. (1949). On the theory of some nonparametric hypotheses. _Annals of Mathematical Statistics, 20_, 28-45. Little, R. J. A. (1989). Testing the equality of two independent binomial proportions. _The American Statistician, 43_, 283-288. Mantel, N. (1967). The detection of disease clustering and a generalized regression approach. _Cancer Research, 27_, 209-220. Mantel, N., & Haenszel, W. (1959). Statistical aspects of the analysis of data from retrospective studies of disease. _Journal of the National Cancer Institute, 22_, 719-748. Mehta, C. R., & Patel, N. R. (1980). A network algorithm for the exact treatment of the 2 x K contingency table. _Communications in Statistics: Simulation and Computation, 9_, 649-664. Mielke, P. W., Berry, K. J., & Johnson, E. S. (1976). Multiresponse permutation procedures for a priori classifications. _Communications in Statistics: Theory and Methods, 5_, 1409-1424. Oden, A., & Wedel, H. (1975). Arguments for Fisher's permutation test. _The Annals of Statistics, 3_, 518-520. Ogawa, J. (1961). Effect of randomization on the analysis of a randomized block design. _Annal Inst Stat Math Tokyo, 13_, 105-117. Pearson, E. S. (1937). Some aspects of the problem of randomization. _Biometrika, 29_, 53-64. Pitman, E. J. G. (1937a). Significance tests which may be applied to samples from any populations. _Journal of the Royal Statistical Society Series B, 4_, 119-130. [R] {This classic paper introduced the Pitman Permutation Test for comparison of the means of two independent samples} Pitman, E. J. G. (1937b). Significance tests which may be applied to samples from any populations II: The correlation coefficient test. _Journal of the Royal Statistical Society Series B, 4_, 225-232. [R] Pitman, E. J. G. (1937c). Significance tests which may be applied to samples from any populations III: The analysis of variance test. _Biometrika, 29_, 322-335. [R] Plackett, R. L. (1968). Random permutations. _Journal of the Royal Statistical Society Series B, 30_, 517-534. Robinson, J. (1972). A converse to a combinatorial central limit theorem. _Annals of Mathematical Statistics, 43_, 2055-2057. Rosenbaum, P. R. (1984). Conditional permutation tests and the propensity score in observational studies. _Journal of the American Statistical Association, 79_, 565-574. Scheffe, H. (1943). Statistical inference in the non-parametric case. _Annals of Mathematical Statistics, 14_, 305-332. Tukey, J. W., Brillinger, D. R., & Jones, L. V. (1978). _Management of Weather Resources, Vol II: The role of statistics in weather resources management_. Washington DC: Department of Commerce, US Government Printing Office. Wald, A., & Wolfowitz, J. (1944). Statistical tests based on permutations of the observations. _Annals of Mathematical Statistics, 15_, 358- 372. Yates, F. (1984). Tests of significance for 2x2 contingency tables (with discussion). _Journal of the Royal Statistical Society Series A, 147_, 426-463. [AT12] {Influential advocacy that randomisation tests on 2x2 tables should be strictly on the basis of conditioning upon the observed marginal totals; there is appended a lengthy discussion} Zelen, M. (1971). The analysis of several 2x2 contingency tables. _Biometrika, 58_, 129-137. [R]