This essential guide on subgroup analyses in the emerging area of
personalized medicine covers the issues of subgroup analyses from a
practical and a theoretical/methodological point of view. The practical
part introduces the issues using examples from the literature where
subgroup analyses led to unexpected or difficult-to-interpret results,
which have been interpreted differently by different stakeholders. On
the technical side, the book addresses selection and selection bias
variance reduction by borrowing information from the full population in
estimating a subgroup effect. To this end, subgroup analysis will be
linked to statistical modelling, and subgroup selection to model
selection. This connection makes the techniques developed for model
selection applicable to subgroup analysis.
Beginning with a history of subgroup analysis, Exploratory Subgroup
Analyses in Clinical Research offers chapters that cover: objectives
and current practice of subgroup analyses; pitfalls of subgroup
analyses; subgroup analysis and modeling; hierarchical models in
subgroup analysis; and selection bias in regression. It also looks at
the predicted individual treatment effect and offers an outlook of the
topic in its final chapter.
- Focuses on the statistical aspects of subgroup analysis
- Filled with classroom and conference-workshop tested material
- Written by a leading expert in the field of subgroup analysis
- Complemented with a companion website featuring downloadable datasets
and examples for teaching use
Exploratory Subgroup Analyses in Clinical Research is an ideal book
for medical statisticians and biostatisticians and will greatly benefit
physicians and researchers interested in personalized medicine.
