Description
Book SynopsisRecent progress in fast, parallel computing and in simulation-based inference has lead to the development of extremely powerful statistical tools. These can now be successfully applied to address the most pressing practical and ethical concerns arising from medical decision problems.
Trade Review"...good to use as one component in a graduate course...for established statisticians and biostatisticians, the book is a good way to get up to speed..." (Journal of the American Statistical Association, March 2007)
"...strongly recommend...[it] to clinical researchers and statisticians." (Journal of Statistical Computation & Simulation, May 2004)
"...I recommend his book." (Statistics in Medicine, 28 February 2003)
"...a comprehensive presentation of topics..." (Clinical Chemistry, Vol. 49, No. 4)
"...an indispensable volume owing to the clarity of its discussion..." (Journal of Drug Assessment, Vol.6, No.4, 2003)
"...another fine practical applications book..." (Technometrics, Vol. 44, No. 4, November 2002)
"...skillfully brings together sophisticated statistical models and detailed medical applications..." (Applied Clinical Trials, June 2002)
"...surveys inferential methods...features case studies..." (SciTech Book News, Vol. 26, No. 2, June 2002)
"...useful to research students in biostatistics...a welcome addition to any undergraduate library in statistics..." (The Statistician)
Table of ContentsPreface.
PART I: METHODS.
1. Inference.
Summary.
Medical Diagnosis.
Genetic Counseling.
Estimating sensitivity and specificity.
Chronic disease modeling.
2. Decision making.
Summary.
Foundations of expected utility theory.
Measuring the value of avoiding a major stroke.
Decision making in health care.
Cost-effectiveness analyses in the SPPM.
Statistical decision problems.
3. Simulation.
Summary.
Inference via simulation.
Prediction and expected utility via simulation.
Sensitivity analysis via simulation.
Searching for strategies via simulation.
Part II: CASE STUDIES.
4. Meta-analysis.
Summary.
Meta-analysis.
Bayesian meta-analysis.
Tamoxifen in early breast cancer.
Combined studies with continuous and dichotomous responses.
Migraine headache.
5. Decision trees.
Summary.
Axillary lymph node dissection in early breast cancer.
A simple decision tree
A more complete decision tree for ALND
6. Chronic disease modeling.
Summary.
Model overview.
Natural history model.
Modeling the effects of screening.
Comparing screening schedules.
Model critique.
Optimizing screening schedule.
References
Index.
