Related references
Note: Only part of the references are listed.Systematic benchmarking of omics computational tools
Serghei Mangul et al.
NATURE COMMUNICATIONS (2019)
Cancer statistics, 2019
Rebecca L. Siegel et al.
CA-A CANCER JOURNAL FOR CLINICIANS (2019)
Projection of cancer incidence rates and case numbers until 2030: A probabilistic approach applied to German cancer registry data (1999-2013)
Christian Stock et al.
CANCER EPIDEMIOLOGY (2018)
On the necessity and design of studies comparing statistical methods
Anne-Laure Boulesteix et al.
BIOMETRICAL JOURNAL (2018)
Bayesian Computing with INLA: A Review
Håvard Rue et al.
Annual Review of Statistics and Its Application (2017)
Projecting the future burden of cancer: Bayesian age-period-cohort analysis with integrated nested Laplace approximations
Andrea Riebler et al.
BIOMETRICAL JOURNAL (2017)
Bayesian penalized spline models for the analysis of spatio-temporal count data
Cici Bauer et al.
STATISTICS IN MEDICINE (2016)
The Growing Burden of Invasive Melanoma: Projections of Incidence Rates and Numbers of New Cases in Six Susceptible Populations through 2031
David C. Whiteman et al.
JOURNAL OF INVESTIGATIVE DERMATOLOGY (2016)
A Review and Comparison of Age-Period-Cohort Models for Cancer Incidence
Theresa R. Smith et al.
STATISTICAL SCIENCE (2016)
Bayesian age-period-cohort models with versatile interactions and long-term predictions: mortality and population in Finland 1878-2050
Aki S. Havulinna
STATISTICS IN MEDICINE (2014)
Cancer incidence in the United Kingdom: projections to the year 2030
M. Mistry et al.
BRITISH JOURNAL OF CANCER (2011)
Constrained Estimators and Age-Period-Cohort Models
Robert M. O'Brien
SOCIOLOGICAL METHODS & RESEARCH (2011)
NORDCAN - a Nordic tool for cancer information, planning, quality control and research
Gerda Engholm et al.
ACTA ONCOLOGICA (2010)
The future burden of cancer in England: incidence and numbers of new patients in 2020
H. Moller et al.
BRITISH JOURNAL OF CANCER (2007)
Low-rank scale-invariant tensor product smooths for generalized additive mixed models
Simon N. Wood
BIOMETRICS (2006)
Bayesian projections: What are the effects of excluding data from younger age groups?
A Baker et al.
AMERICAN JOURNAL OF EPIDEMIOLOGY (2005)
Lung cancer rate predictions using generalized additive models
MS Clements et al.
BIOSTATISTICS (2005)
Prediction of cancer incidence in the Nordic countries:: empirical comparison of different approaches
B Moller et al.
STATISTICS IN MEDICINE (2003)
Share Paper
