Statistical and epidemiological methodology

The analysis [14] involved possibly the earliest application of the Weibull distribution, that is the model that mesothelioma incidence increases as a power of time since exposure, to asbestos. This power relationship was used as a means of planning experiments in a statistical methods paper [34].

14. BERRY, G. & WAGNER, J.C. (1969). The application of a mathematical model describing the times of occurrence of mesotheliomas in rats following inoculation with asbestos. Br. J. Cancer, 23, 582-6.

17. BERRY, G. (1970). Parametric analysis of disease incidences in multiway tables. Biometrics, 26, 572-9.

25. BERRY, G. & DAY, N.E. (1973). The statistical analysis of the results of sampling an environment for a contaminant when most samples contain an undetectable level. Am. J. Epidemiol., 97, 160-6.

33. BERRY, G. (1974). Longitudinal observations. Their usefulness and limitations with special reference to the forced expiratory volume. Bull. Physio path. resp., 10, 643-56.

34. BERRY, G. (1975). Design of carcinogenesis experiments using the Weibull distribution. Biometrika, 62, 321-8.

50. BERRY, G. (1980). Dose response in case control studies. J. Epidemiol. Commun. Hlth., 34, 217-22. PDF

67. BERRY, G. (1983). The analysis of mortality by the subject years method. Biometrics, 39, 173-84.

74. BERRY, G., MANDRYK, J. & MOCK, P. (1985). Presentation of results of log linear models: analyses of cohort and cross sectional studies. In: Statcomp Medstat 85 Symposium Proceedings, 56-64. Stat. Soc. Australia.

76. BERRY, G., MANDRYK, J.A. & MOCK, P. (1986). Presentation of results of logistic regression: analyses of cohort and cross sectional studies. In: Proceedings of Pacific Statistical Conference, Auckland, 1985, eds. I.S. Francis, B.F.J. Manly and F.C. Lam, 79-82. Elsevier, North Holland.

77. BERRY, G. (1986). Statistical significance and confidence intervals. Med. J. Aust., 144, 618 9. [reprinted in Br. J. Clin. Pract. 1988, 42, 465-8]

106. BERRY, G., KITCHIN, R.M. & MOCK, P.A. (1991). A comparison of two simple hazard ratio estimators based on the logrank test. Statist. Med., 10, 749-55.

120. IRWIG, L., GLASZIOU, P.P., BERRY, G., CHOCK, C., MOCK, P. & SIMPSON, J.M. (1994). Efficient study designs to assess the accuracy of screening tests. Am. J. Epidemiol., 140, 759-769. (Erratum 141, 697)

124. BERRY, G. & ARMITAGE, P. (1995) Mid-P confidence intervals: a brief review. The Statistician (JRSS Series D), 44, 417-423.

131. DE BURGH, S. & BERRY, G. (1997). Treating grouped data as continuous in alcohol consumption measures. Addiction, 92, 667-672.

135. CHOCK, C., IRWIG, L., BERRY, G. & GLASZIOU, P. (1997). Comparing dichotomous screening tests when individuals negative on both tests are not verified. J. Clin. Epidemiol., 50, 1211-1217.

144. SENETA, E., BERRY, G. & MACASKILL, P. (1999). Adjustment to Lancaster's mid-P. Methodol. Comput. Appl. Probab., 1, 229-240.

158. BERRY, G., SMITH, C.L., MACASKILL, P. & IRWIG, L. (2002). Analytic methods for comparing two dichotomous screening or diagnostic tests applied to two populations of differing disease prevalence when individuals negative on both tests are unverified. Stat. Med., 21, 853-862.

164. HAYES, L.J. & BERRY, G. (2002). Sampling variability of the Kunst-Mackenbach relative index of inequality. J. Epidemiol. Community Health, 56, 762-765. PDF

181. HAYES, L.J. & BERRY, G. (2006). Comparing the part with the whole: should overlap be ignored in public health measures? J. Publ. Hlth., 28, 278-282. Abstract PDF

184. BERRY, G. (2007). Relative risk and acceleration in lung cancer. Stat. Med., 26, 3511-3517. Abstract

C1 BERRY, G. (1981). Statistical analyses. In: Occupational Lung Diseases: Research Approaches and Methods, eds. H. Weill and M. Turner Warwick, 427-63. Marcel Dekker, New York.

C8a BERRY, G. (1998). In: Handbook of Public Health Methods, eds. C. Kerr, R. Taylor & G. Heard. McGraw-Hill, Sydney.
Unit 44, Trends in proportions: ordered groups, 267-269;
Unit 54, Combining 2 x 2 Tables, 335-339;
Unit 55, Generalized linear models, 340-343;
Unit 56, Logistic regression, 344-349.

C8b BERRY, G. & SIMPSON, J. (1998). In: Handbook of Public Health Methods, eds. C. Kerr, R. Taylor & G. Heard. McGraw-Hill, Sydney.
Unit 22, Variables, 145-146;
Unit 26, Summarizing data in figures and tables, 169-177;
Unit 27, Summarizing continuous variables, 178-183;
Unit 35, Sampling and sampling error, 217-219;
Unit 36, Sample size calculation, 220-227;
Unit 37, Confidence intervals and statistical significance, 228-234;
Unit 38, Confidence interval for a proportion, 235-237;
Unit 39, Comparison of paired means: paired t-test, 238-240;
Unit 40, Comparison of paired proportions, 241-247;
Unit 41, Comparison of two independent means: 2-sample t-test, 248-252;
Unit 42, Comparison of two independent proportions, 253-259;
Unit 49, Forms of independent variables, 302-304;
Unit 52, Modeling strategy, 321-330.

C8c BERRY, G. & TAYLOR, R.J. (1998). In: Handbook of Public Health Methods, eds. C. Kerr, R. Taylor & G. Heard. McGraw-Hill, Sydney.
Unit 57, Poisson regression, 350-353.

C8d SIMPSON, J. & BERRY, G. (1998). In: Handbook of Public Health Methods, eds. C. Kerr, R. Taylor & G. Heard. McGraw-Hill, Sydney.
Unit 31, Probability, 197-203;
Unit 32, Binomial distribution, 204-207;
Unit 33, Poisson distribution, 208-211;
Unit 34, Normal distribution, 212-216;
Unit 43, Distribution-free or non-parametric tests, 260-266;
Unit 45, Selecting appropriate tests, 270-273;
Unit 47, Simple regression and correlation, 288-295;
Unit 48, Multiple linear regression, 296-301;
Unit 50, One-way analysis of variance, 305-311;
Unit 51, Analysis of covariance, 312-320;
Unit 53, Examination of residuals to check regression assumptions, 331-334.

C8e TAYLOR, R.J. & BERRY, G. (1998). In: Handbook of Public Health Methods, eds. C. Kerr, R. Taylor & G. Heard. McGraw-Hill, Sydney.
Unit 71, Quantitative meta-analysis, 449-456.

C9 BERRY, G. (2000). Analysis and interpretation. In: Epidemiology of Work Related Diseases, 2nd edn, ed. J.C. McDonald, 511-532. BMJ Publishing Group, London.

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