Kelly, P. J. and Lim, L. L. Y. (2000).
Survival analysis for recurrent event data: an application to childhood infectious diseases
Statistics Medicine (Volume 19) pp. 13-33

Aarons, L. (1999).
Software for population pharmacokinetics and pharmacodynamics
Clinical Pharmacokinetics (Volume 36) pp. 255-264

Auranen, K. and Eichner, M. and Kayhty, H. and Takala, A. K. and Arjas, E. (1999).
A hierarchical bayesian model to predict the duration of immunity to haemophilus influenzae type b
Biometrics (Volume 55) pp. 1306-1313

Blettner, M. and Sauerbrei, W. and Schlehofer, B. and Scheuchenpflug, T. and Friedenreich, C. (1999).
Traditional reviews, meta-analyses and pooled analyses in epidemiology
International J. Epidemiology (Volume 28) pp. 1-9

Brumback, B. A. and Holmes, L. B. and Ryan, L. M. (1999).
Adverse effects of chorionic villus sampling: a meta- analysis
Statistics Medicine (Volume 18) pp. 2163-2175

Burroughs, N. J. and Pillay, D. and Mutimer, D. (1999).
Significance testing of clinical data using virus dynamics models with a markov chain monte carlo method: application to emergence of lamivudine-resistant hepatitis b virus
Proceedings Royal Soc. London Series B-Biological Sciences (Volume 266) pp. 2359-2366

Cowles, M. K. and Roberts, G. O. and Rosenthal, J. S. (1999).
Possible biases induced by mcmc convergence diagnostics
J. Statistical Computation Simulation (Volume 64) pp. 87-104

Dominici, F. and Parmigiani, G. and Wolpert, R. L. and Hasselblad, V. (1999).
Meta-analysis of migraine headache treatments: combining information from heterogeneous designs
J. Amer. Statistical Association (Volume 94) pp. 16-28

George, A. W. and Mengersen, K. L. and Davis, G. P. (1999).
A bayesian approach to ordering gene markers
Biometrics (Volume 55) pp. 419-429

Ghosh, M. and Natarajan, K. and Waller, L. A. and Kim, D. (1999).
Hierarchical bayes glms for the analysis of spatial data: an application to disease mapping
J. Statistical Planning Inference (Volume 75) pp. 305-318

Goodman, S. N. (1999).
Toward evidence-based medical statistics. 2: the bayes factor
Annals Internal Medicine (Volume 130) pp. 1005-1013

Haario, H. and Saksman, E. and Tamminen, J. (1999).
Adaptive proposal distribution for random walk metropolis algorithm
Computational Statistics (Volume 14) pp. 375-395

Holsinger, K. E. (1999).
Analysis of genetic diversity in geographically structured populations: a bayesian perspective
Hereditas (Volume 130) pp. 245-255

Hughes, J. P. (1999).
Mixed effects models with censored data with application to hiv rna levels
Biometrics (Volume 55) pp. 625-629

Jordan, M. I. and Ghahramani, Z. and Jaakkola, T. S. and Saul, L. K. (1999).
An introduction to variational methods for graphical models
Machine Learning (Volume 37) pp. 183-233

Langford, I. H. and Leyland, A. H. and Rasbash, J. and Goldstein, H. (1999).
Multilevel modelling of the geographical distributions of diseases
J. Royal Statistical Soc. Series C-Applied Statistics (Volume 48) pp. 253-268

Liao, J. G. (1999).
A hierarchical bayesian model for combining multiple 2 x 2 tables using conditional likelihoods
Biometrics (Volume 55) pp. 268-272

Lipsitch, M. (1999).
Bacterial vaccines and serotype replacement: lessons from haemophilus influenzae and prospects for streptococcus pneumoniae
Emerging Infectious Diseases (Volume 5) pp. 336-345

Madigan, D. (1999).
Bayesian data mining in large frequency tables, with an application to the fda spontaneous reporting system – discussion
Amer. Statistician (Volume 53) pp. 198-200

Martz, H. F. and Parker, R. L. and Rasmuson, D. M. (1999).
Estimation of trends in the scram rate at nuclear power plants
Technometrics (Volume 41) pp. 352-364

Millar, R. B. and Willis, T. J. (1999).
Estimating the relative density of snapper in and around a marine reserve using a log-linear mixed-effects model
Australian & New Zealand J. Statistics (Volume 41) pp. 383-394

Plewis, L. and Raab, G. (1999).
Editorial: modelling structured categorical data [full text available, price (pounds)17.63]
J. Royal Statistical Soc. Series A-Statistics Society (Volume 162) pp. 269-271

Pollan, M. and Lopezabente, G. and Aragones, N. and Ruiz, M. (1999).
Malignant brain tumour mortality among children and adolescents: geographical distribution in spain
J. Neurological Sciences (Volume 163) pp. 127-136

Sahu, S. K. and Roberts, G. O. (1999).
On convergence of the em algorithm and the gibbs sampler
Statistics Computing (Volume 9) pp. 55-64

Shoemaker, J. S. and Painter, I. S. and Weir, B. S. (1999).
Bayesian statistics in genetics – a guide for the uninitiated
Trends Genetics (Volume 15) pp. 354-358

Tritchler, D. (1999).
Reasoning about data with directed graphs
Statistics Medicine (Volume 18) pp. 2067-2076

Zhou, X. H. and Perkins, A. J. and Hui, S. L. (1999).
Comparisons of software packages for generalized linear multilevel models
Amer. Statistician (Volume 53) pp. 282-290

Ashby, D. and Smyth, R. L. and Brown, P. J. (1998).
Statistical issues in pharmacoepidemiological case-control studies
Statistics Medicine (Volume 17) pp. 1839-1850

Brooks, S. P. (1998).
Markov chain monte carlo method and its application
Statistician (Volume 47) pp. 69-100

Burton, P. R. and Gurrin, L. C. and Campbell, M. J. (1998).
Clinical significance not statistical significance: a simple bayesian alternative to p values
J. Epidemiology Community Health (Volume 52) pp. 318-323

Chen, M. H. and Schmeiser, B. (1998).
Toward black-box sampling: a random-direction interior-point markov chain approach
J. Computational Graphical Statistics (Volume 7) pp. 1-22

Curran, J. M. and Triggs, C. M. and Buckleton, J. S. and Walsh, K. A. J. and Hicks, T. (1998).
Assessing transfer probabilities in a bayesian interpretation of forensic glass evidence
Science & Justice (Volume 38) pp. 15-21

Ghosh, M. and Natarajan, K. and Stroud, T. W. F. and Carlin, B. P. (1998).
Generalized linear models for small-area estimation
J. Amer. Statistical Association (Volume 93) pp. 273-282

Gilks, W. R. and Roberts, G. O. and Suhu, S. K. (1998).
Adaptive markov chain monte carlo through regeneration
J. Amer. Statistical Association (Volume 93) pp. 1045-1054

Gilks, W. R. and Roberts, G. O. and Suhu, S. K. (1998).
Adaptive markov chain monte carlo through regeneration
J. Amer. Statistical Association (Volume 93) pp. 1045-1054

Greenwood, P. E. and McKeague, I. W. and Wefelmeyer, W. (1998).
Information bounds for gibbs samplers
Annals Statistics (Volume 26) pp. 2128-2156

Jensen, C. S. (1998).
A simple method for finding a legal configuration in complex bayesian networks
Statistics Computing (Volume 8) pp. 243-251

Kass, R. E. and Carlin, B. P. and Gelman, A. and Neal, R. M. (1998).
Markov chain monte carlo in practice: a roundtable discussion
Amer. Statistician (Volume 52) pp. 93-100

Kaufman, D. E. and Smith, R. L. (1998).
Direction choice for accelerated convergence in hit-and-run sampling
Operations Research (Volume 46) pp. 84-95

Krause, P. J. (1998).
Learning probabilistic networks
Knowledge Engineering Review (Volume 13) pp. 321-351

MacKay, D. J. C. and Takeuchi, R. (1998).
Interpolation models with multiple hyperparameters
Statistics Computing (Volume 8) pp. 15-23

Muller, P. and Insua, D. R. (1998).
Issues in bayesian analysis of neural network models
Neural Computation (Volume 10) pp. 749-770

Thompson, J. R. (1998).
Invited commentary: re: ”multiple comparisons and related issues in the interpretation of epidemiologic data”
Amer. J. Epidemiology (Volume 147) pp. 801-806

Bashir, S. A. and Duffy, S. W. (1997).
The correction of risk estimates for measurement error
Annals Epidemiology (Volume 7) pp. 154-164

Christiansen, C. L. and Morris, C. N. (1997).
Improving the statistical approach to health care provider profiling
Annals Internal Medicine (Volume 127) pp. 764-768

Daniels, M. J. and Gatsonis, C. (1997).
Hierarchical polytomous regression models with applications to health services research
Statistics Medicine (Volume 16) pp. 2311-2325

Daniels, M. J. and Hughes, M. D. (1997).
Meta-analysis for the evaluation of potential surrogate markers
Statistics Medicine (Volume 16) pp. 1965-1982

Christiansen, O. B. (1997).
Epidemiological, immunogenetic and immunotherapeutic aspects of unexplained recurrent miscarriage
Danish Medical Bulletin (Volume 44) pp. 396-424

Christiansen, C. L. and Morris, C. N. (1997).
Hierarchical poisson regression modeling
J. Amer. Statistical Association (Volume 92) pp. 618-632

Heckerman, D. (1997).
Bayesian networks for data mining
Data Mining Knowledge Discovery (Volume 1) pp. 79-119

Lazaridis, E. N. and Gonin, R. (1997).
Continuously monitored stopping boundary methodologies: the issues of sensitivity, association and trial suspension
Statistics Medicine (Volume 16) pp. 1925-1941

Malec, D. and Sedransk, J. and Moriarity, C. L. and Leclere, F. B. (1997).
Small area inference for binary variables in the national health interview survey
J. Amer. Statistical Association (Volume 92) pp. 815-826

Ramoni, M. and Sebastiani, P. (1997).
The use of exogenous knowledge to learn bayesian networks from incomplete databases
Lecture Notes Computer Science (Volume 1280) pp. 537-548

Vanhouwelingen, H. C. (1997).
The future of biostatistics: expecting the unexpected
Statistics Medicine (Volume 16) pp. 2773-2784

Athreya, K. B. and Doss, H. and Sethuraman, J. (1996).
On the convergence of the markov chain simulation method
Annals Statistics (Volume 24) pp. 69-100

Berzuini, C. and Larizza, C. (1996).
A unified approach for modeling longitudinal and failure time data, with application in medical monitoring
Ieee Trans. On Pattern Analysis Machine Intelligence (Volume 18) pp. 109-123

Brewer, M. J. and Aitken, C. G. G. and Talbot, M. (1996).
A comparison of hybrid strategies for gibbs sampling in mixed graphical models
Computational Statistics & Data Analysis (Volume 21) pp. 343-365

Buntine, W. (1996).
A guide to the literature on learning probabilistic networks from data
Ieee Trans. On Knowledge Data Engineering (Volume 8) pp. 195-210

Cowles, M. K. (1996).
Accelerating monte carlo markov chain convergence for cumulative-link generalized linear models
Statistics Computing (Volume 6) pp. 101-111

Engel, B. and Keen, A. and Clayton, D. and Londford, N. T. and Kuba, J. and Firth, D. and Draper, D. and Atkinson, A. C. and Raab, G. M. and Parpia, T. and Choy, S. T. B. and Smith, A. F. M. and Dale, J. R. and Shephard, N. and Ball, R. D. and Breslow, N. E. and Ekholm, A. and Gelman, A. and Langford, I. H. and Morris, C. N. and Preece, D. A. and Seu, P. K. and Smith, R. L. and Thompson, R. and Walker, S. G. and Mallick, B. K. and Lee, Y. and Nelder, J. A. (1996).
Hierarchical generalized linear models – discussion
J. Royal Statistical Soc. Series B-Methodological (Volume 58) pp. 656-678

Hendricks, S. A. and Wassell, J. T. and Collins, J. W. and Sedlak, S. L. (1996).
Sampling from the posterior distribution in generalized linear mixed models
Statistics Medicine (Volume 15) pp. 1951-1960

Kleiter, G. D. (1996).
Propagating imprecise probabilities in bayesian networks
Artificial Intelligence (Volume 88) pp. 143-161

Pettitt, A. N. (1996).
Infinite estimates with fractional factorial experiments
Statistician (Volume 45) pp. 197-206

Sabin, C. A. and Ashby, D. and Richardson, S. and Guihenneucjouyaux, C. and Hansfordmiller, F. and Lawless, J. F. and Yan, P. and Bertrand, P. V. and Aalen, O. O. and Berzuini, C. and Gobbi, C. and Gigli, A. and Gilks, W. R. and Deangelis, D. and Newton, M. A. and Vandepol, F. and Segal, M. R. and Solomon, P. J. and Taylor, J. M. G. (1996).
Markov chains with measurement error: estimating the ‘true’ course of a marker of the progression of human immunodeficiency virus disease – discussion
Applied Statistics-J. Royal Statistical Soc. Series C (Volume 45) pp. 295-309

Severini, T. A. and Tanner, M. A. (1996).
Empirical bayes methods for combining likelihoods – comment
J. Amer. Statistical Association (Volume 91) pp. 560-562

Dawid, A. P. and Kjaerulff, U. and Lauritzen, S. L. (1995).
Hybrid propagation in junction trees
Lecture Notes Computer Science (Volume 945) pp. 87-97

Draper, D. (1995).
Assessment and propagation of model uncertainty
J. Royal Statistical Soc. Series B-Methodological (Volume 57) pp. 45-97

Etzioni, R. D. and Kadane, J. B. (1995).
Bayesian statistical-methods in public-health and medicine
Annual Review Public Health (Volume 16) pp. 23-41

Jensen, C. S. and Kjaerulff, U. and Kong, A. (1995).
Blocking gibbs sampling in very large probabilistic expert- systems
International J. Human-Computer Studies (Volume 42) pp. 647-666

Jones, D. R. (1995).
Metaanalysis – weighing the evidence
Statistics Medicine (Volume 14) pp. 137-149

Chevrolat, J. P. and Rutigliano, F. and Golmard, J. L. (1994).
Mixed bayesian networks – a mixture of gaussian distributions
Methods Information Medicine (Volume 33) pp. 535-542

Raab, G. M. and Elton, R. A. (1993).
Bayesian-analysis of binary data from an audit of cervical smears
Statistics Medicine (Volume 12) pp. 2179-2189

Richardson, S. and Gilks, W. R. (1993).
Conditional-independence models for epidemiologic studies with covariate measurement error
Statistics Medicine (Volume 12) pp. 1703-1722

Spiegelhalter, D. J. and Dawid, A. P. and Lauritzen, S. L. and Cowell, R. G. (1993).
Bayesian-analysis in expert-systems
Statistical Science (Volume 8) pp. 219-247

Gilks, W. R. and Richardson, S. (1992).
Analysis of disease risks using ancillary risk-factors, with application to job exposure matrices
Statistics Medicine (Volume 11) pp. 1443-1463