Cox proportional hazards

• time-varying covariates and censoring
• Continuously time-varying covariates
• conventional or robust estimates of variance
• stratified estimation
• Sampling weights and survey data
  
• four ways to handle ties: Breslow, exact partial likelihood, exact marginal likelihood, and Efron
• martingale, efficient score, Cox–Snell, Schoenfeld, and deviance residuals
• tests for proportional hazards
• estimates of baseline survival, hazard, and cumulative hazard functions
• shared frailty models
• Harrell’s C, Somers’ D, and Gönen and Heller’s K statistics measuring concordance
• Multiple imputation

• Fine and Gray proportional subhazards model
  
• Time-varying covariates
  
• Cumulative-incidence graphs
  
• Subhazard ratios
  
• Multiple imputation  
  
• Constraints
  

Parametric survival models

• exponential
• Weibull
• Gompertz
• lognormal
• loglogistic
• generalized log-gamma
• Sampling weights and survey data
  
• martingale-like, score, Cox–Snell, Schoenfeld, and deviance residuals
• plots of predicted survival, hazard, and cumulative hazard functions
• individual-level frailty
• group-level or shared frailty
• stratified models
• linear constraints

Features of survival models

• single or multiple failure data
• left truncation
• right censoring
• time-varying regressors
• gaps
• recurring events
• start-stop format
• different types of failure events
• multiple time scales allowed
• conventional or robust estimates of variance

• Analysis of main effects, simple effects, interaction effects, partial interaction effects, and nested effects
  
• Comparisons against reference groups, of adjacent levels, or against the grand mean
  
• Orthogonal polynomials
  
• Helmert contrasts
  
• Custom contrasts
  
• ANOVA-style tests
  
• Contrasts of nonlinear responses
  
• Multiple-comparison adjustments
  
• Balanced and unbalanced data
  
• Contrasts in odds-ratio metric
  
• Contrasts of means, intercepts, and slopes
  
• Graphs of contrasts
  
• Interaction plots
  

• Compare estimated means, intercepts, and slopes
  
• Compare marginal means, intercepts, and slopes
  
• Balanced and unbalanced data
  
• Nonlinear responses
  
• Multiple-comparison adjustments: Bonferroni, Šidák, Scheffé, Tukey HSD, Duncan, and Student-Newman-Keuls adjustments
  
• Group comparisons that are significant
  
• Graphs of pairwise comparisons

Kaplan–Meier survival curves

• graph estimates and confidence intervals
• Confidence bands
  
• Embedded risk tables
  
• Adjustments for confounders
  
• Stratification
  
• Nelson–Aalen graphs of cumulative hazards
  

Life tables and analysis

• Graphs and tables of estimates and confidence intervals
  
• Mean survival times and confidence intervals
  
• Cox regression adjustments
  
• Actuarial adjustments
  
• Tests for trend
  
• Tests of equality—log-rank, Mantel–Haenszel, Wilcoxon–Breslow, Tarone–Ware, Fleming–Harrington, Peto–Peto–Prentice
  

• Solve for sample size, power, or effect size
• Log-rank test of survival curves
• Cox proportional hazards model
• Exponential regression
• Time at risk, incidence rate, number of subjects, 25th, 50th, and 75th percentiles of survival time
• Incidence-rate ratio and difference
• Life tables
• Rates and SMRs by one or more categorical variables
• Stratified rate ratios
  

Utilities

• create nested case-control datasets
• split and join time records
• conver snapshot data into time-span data
• calculate person-time (person-years), incidence rates, and standardized mortality/morbidity ratios (SMR)

Predictions and estimates

• mean or median time to failure
• mean or median log time
• hazard
• hazard ratios
• survival probabilities

• Automatically create indicators based on categorical variables
  
• Form interactions among discrete and continuous variables
  
• Include polynomial terms
  
• Perform contrasts of categories/levels
  

• Estimated marginal means
  
• Marginal and partial effects
  
• Average marginal and partial effects
  
• Least-squares means
  
• Predictive margins
  
• Adjusted predictions, means, and effects
  
• Contrasts of margins*
• Pairwise comparisons of margins*
• Profile plots*
• Graphs of margins and marginal effects*