Publications

Geweke, J 1992, Decision Making under Risk and Uncertainty: New Models and Empirical Findings., Kluwer Academic Publishers, Dordrecht.

Geweke, J 1992, 'Evaluating the Accuracy of Sampling-Based Approaches to the Calculation of Posterior Moments' in Bernardo, JM, Berger, JO, Dawid, AP & Smith, AFM (eds), Bayesian Statistics 4, Oxford University Press, Oxford, pp. 169-194.
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Abstract: Data augmentation and Gibbs sampling are two closely related, sampling-based approaches to the calculation of posterior moments. The fact that each produces a sample whose constituents are neither independent nor identically distributed complicates the assessment of convergence and numerical accuracy of the approximations to the expected value of functions of interest under the posterior. In this paper methods from spectral analysis are used to evaluate numerical accuracy formally and construct diagnostics for convergence. These methods are illustrated in the normal linear model with informative priors, and in the Tobit-censored regression model.

Borden, EC, Kim, K, Ryan, LM, Blum, RH, Shiraki, M, Tormey, DC, Comis, RH, Hahn, RG & Parkinson, DR 1992, 'Phase II trials of interferons-alpha and -beta in advanced sarcomas', Journal of Interferon Research, vol. 12, no. 6, pp. 455-458.
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Catalano, PJ & Ryan, LM 1992, 'Bivariate latent variable models for clustered discrete and continuous outcomes', Journal of the American Statistical Association, vol. 87, no. 419, pp. 651-658.
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We use the concept of a latent variable to derive the joint distribution of a continuous and a discrete outcome, and then extend the model to allow for clustered data. The model Can be parameterized in a way that allows one to write the joint distribution as a product of a standard random effects model for the continuous variable and a correlated probit model for the discrete variable. This factorization suggests a convenient approach to parameter estimation using quasi-likelihood techniques. Our approach is motivated by the analysis of developmental toxicity experiments for which a number of discrete and continuous outcomes are measured on offspring clustered within litters. Fetal weight and malformation data illustrate the results.

Catalano, PJ & Ryan, LM 1992, 'Bivariate latent variable models for clustered discrete and continuous outcomes', Journal of the American Statistical Association, vol. 87, no. 419, pp. 651-658.
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We use the concept of a latent variable to derive the joint distribution of a continuous and a discrete outcome, and then extend the model to allow for clustered data. The model can be parameterized in a way that allows one to write the joint distribution as a product of a standard random effects model for the continuous variable and a correlated probit model for the discrete variable. This factorization suggests a convenient approach to parameter estimation using quasi-likelihood techniques. Our approach is motivated by the analysis of developmental toxicity experiments for which a number of discrete and continuous outcomes are measured on offspring clustered within litters. Fetal weight and malformation data illustrate the results. © 1992 Taylor & Francis Group, LLC.

DAGOSTINO, RB, LANGE, N & RYAN, L 1992, 'PAPERS FROM THE SYMPOSIUM ON LONGITUDINAL DATA-ANALYSIS, 19-21 JUNE 1991 - OVERVIEW', STATISTICS IN MEDICINE, vol. 11, no. 14-15, pp. 1801-1805.
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D'agostino, RB, Lange, N & Ryan, L 1992, 'Overview', Statistics in Medicine, vol. 11, no. 14-15, pp. 1801-1805.
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D'agostino, RB, Lange, N & Ryan, LM 1992, 'Overview', Statistics in Medicine, vol. 11, pp. 1801-1805.

Falkson, G, Ryan, LM & Haller, D 1992, 'Phase-ii Trial For The Evaluation Of Trimetrexate In Patients With Inoperable Squamous Carcinoma Of The Esophagus', American Journal Of Clinical Oncology-cancer Clinical Trials, vol. 15, no. 5, pp. 433-435.
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EST 2287 was a Phase II clinical trial conducted by the Eastern Cooperative Oncology Group (ECOG) designed to evaluate trimetrexate in patients with advanced, measurable, inoperable squamous cell carcinoma of the esophagus. The drug was given at a dose o

Geweke, J 1992, 'Comment: Inference and prediction in the presence of uncertainty and determinism', Statistical Science, vol. 7, no. 1, pp. 94-101.
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Geweke, J 1992, 'Editor’s report', Journal of Business and Economic Statistics, vol. 10, no. 4, p. 375.
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Geweke, J 1992, 'Inference and Prediction in the Presence of Uncertainty and Determinism', Statistical Science, vol. 7, pp. 94-101.

GOPALSAMY, K, HE, XZ & WEN, LZ 1992, 'GLOBAL ATTRACTIVITY AND LEVEL-CROSSINGS IN A PERIODIC LOGISTIC INTEGRODIFFERENTIAL EQUATION', MATHEMATISCHE NACHRICHTEN, vol. 156, pp. 25-44.
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Leisenring, W & Ryan, LM 1992, 'Statistical properties of the NOAEL', Regulatory Toxicology and Pharmacology, vol. 15, pp. 161-171.
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RYAN, L 1992, 'THE USE OF GENERALIZED ESTIMATING EQUATIONS FOR RISK ASSESSMENT IN DEVELOPMENTAL TOXICITY', RISK ANALYSIS, vol. 12, no. 3, pp. 439-447.
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Ryan, LM 1992, 'Quantitative risk assessment for developmental toxicity', Biometrics, vol. 48, pp. 163-174.
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Pharmaceutical companies and governmental regulatory agencies are becoming increasingly aware of the need for improved statistical methods for developmental toxicity experiments. Although a number of statisticians have become interested in this area, activity has centered mostly on the development of methods to analyze binary outcomes, such as malformations among live pups, while accounting appropriately for the correlation induced by the litter effect. In contrast, the topic of quantitative risk assessment has received relatively little attention. This paper addresses the specific question of how to assess risk appropriately when exposure causes a variety of adverse effects, including resorption and fetal death, in addition to malformations. It will be seen that risk assessments based on a single developmental outcome, such as malformation, may be conservative. A method is proposed for estimating an exposure level at which the overall risk of any adverse effect is acceptably low. The method is based on a continuation ratio formulation of a multinomial distribution, with an additional scale parameter to account for overdispersion. Comparisons are made with binary models on prenatal death and malformation, as well as a binary model that makes no distinction between death and malformation, but simply classifies each fetus as normal or abnormal. Data from several developmental toxicity studies illustrate the results and findings.

Zhang, C 1992, 'Cooperation Under Uncertainty In Distributed Expert Systems', Artificial Intelligence, vol. 56, pp. 21-69.
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