incAnalysis

incAnalysis implements in R a comparative evaluation of statistical approaches for projecting cancer incidence rates to inform cancer epidemiology and public health planning.

Key Features:

• Model Comparison: Supports comparative analysis of statistical models including Bayesian Age-Period-Cohort (BAPC) models and assessment using short-term data when long-term registry data are unavailable.
• Bayesian Framework Support: Emphasizes Bayesian models fitted by Integrated Nested Laplace Approximations (INLA) to perform statistical inference and incidence projection.
• Empirical Evaluation: Facilitates empirical assessment of operating characteristics such as bias, coverage, and precision across models.

Scientific Applications:

• Epidemiological Research: Enables evaluation and selection of projection approaches suited to cancer incidence studies and varying data availability.
• Public Health Policy: Provides comparative projections to inform resource allocation and policy planning for cancer incidence trends.

Methodology:

Benchmarks statistical approaches, including BAPC models fitted with INLA, against observed long-term cancer registry data (SEER-9, NORDCAN, Saarland) and evaluates operating characteristics (bias, coverage, precision) to assess projection performance with short-term data.