Quantitative methods play an important role in the fields of epidemiology and statistics. The intent of this review series is to provide readers with clearly written chapters on classical statistical and epidemiologic methods as well as new techniques in the literature that are not currently covered in standard textbooks in the field.
Example topics of interest include:
• Randomized clinical trials
• Gene-environment interaction studies
• Longitudinal studies
• Cohort studies
• Case-only studies
• Case-referent studies
• Misclassification bias
• Selection bias
• Confounding by indication
• Population-projection methods
• Poisson / log-binomial regression
• Beta-binomial regression
• Logistic regression
• Survival analysis
• Sample size computation
• Sinusoidal models
• Log-linear models
• Attributable risk and fractions
• Sampling design and error
• Outcome measures and models
• Mantel-Haenszel methods
• Matched-set designs and analysis
• Rates and proportions
• Propensity scores
• Complex samples
• Advanced multivariate models
• Modeling overdispersion
• Bootstrap / jack-knife methods
• Generalized additive models
• Mixed-effect models
• Imputation methods
• Non-proportional hazards models
• Direct and indirect adjustment
• Additive and multiplicative models
• Directed acyclic graphs
• Conditional models
• Bayesian analysis and power computation
• Simulation methods
• Exact relative effects models
• Gatekeeper and other strategies for multiplicity adjustment
• Study design and analysis
• Generalized linear models for non-normal distributed data
• Hierarchical / multilevel models
• Age period and age-cohort models
• Blocked randomization with randomly selected block sizes
• Space-time and geographic risk analysis
• Risk stratification models
• Non-parametric risk assessment
• Proportional-odds models
• Exact discrete regression
• Lasso Methods
• Path analysis and structural equation modeling
• Genotype analysis
• Transmission Disequilibrium Test
• Multivariate outlier detection
• Informational odds ratios
• Two-stage sampling designs
• Classification trees
• Random forest algorithm
• Simulation methods for complex power analysis
• Discriminant analysis
• Factor analysis
• Principal components regression
• Closed testing methods
Quantitative methods play an important role in the fields of epidemiology and statistics. The intent of this review series is to provide readers with clearly written chapters on classical statistical and epidemiologic methods as well as new techniques in the literature that are not currently covered in standard textbooks in the field.
Example topics of interest include:
• Randomized clinical trials
• Gene-environment interaction studies
• Longitudinal studies
• Cohort studies
• Case-only studies
• Case-referent studies
• Misclassification bias
• Selection bias
• Confounding by indication
• Population-projection methods
• Poisson / log-binomial regression
• Beta-binomial regression
• Logistic regression
• Survival analysis
• Sample size computation
• Sinusoidal models
• Log-linear models
• Attributable risk and fractions
• Sampling design and error
• Outcome measures and models
• Mantel-Haenszel methods
• Matched-set designs and analysis
• Rates and proportions
• Propensity scores
• Complex samples
• Advanced multivariate models
• Modeling overdispersion
• Bootstrap / jack-knife methods
• Generalized additive models
• Mixed-effect models
• Imputation methods
• Non-proportional hazards models
• Direct and indirect adjustment
• Additive and multiplicative models
• Directed acyclic graphs
• Conditional models
• Bayesian analysis and power computation
• Simulation methods
• Exact relative effects models
• Gatekeeper and other strategies for multiplicity adjustment
• Study design and analysis
• Generalized linear models for non-normal distributed data
• Hierarchical / multilevel models
• Age period and age-cohort models
• Blocked randomization with randomly selected block sizes
• Space-time and geographic risk analysis
• Risk stratification models
• Non-parametric risk assessment
• Proportional-odds models
• Exact discrete regression
• Lasso Methods
• Path analysis and structural equation modeling
• Genotype analysis
• Transmission Disequilibrium Test
• Multivariate outlier detection
• Informational odds ratios
• Two-stage sampling designs
• Classification trees
• Random forest algorithm
• Simulation methods for complex power analysis
• Discriminant analysis
• Factor analysis
• Principal components regression
• Closed testing methods
