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
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message: send exact-stats bibliogen.txt
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===========================================================================
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]