1 item has been added to your cart.

• Introduction
• The problem of survival analysis
• The need for specific distributions
• Answering specific kinds of questions
• Censoring
• Right-censoring (withdrawal from study)
• Left-censoring
• Truncation
• Left-truncation (delayed entry)
• Right-truncation
• Gaps
• Survival analysis
• The survivor and hazard functions
• Hazard models
• Parametric models
• Semiparametric models
• Nonparametric estimators
• Analysis time (time at risk)
• Summary

• The purpose of the stset command
  • The desired format—Introduction to stset
  • (st) Setting your data
  • The syntax of the stset command
    • Specifying analysis time
    • Specifying what constitutes failure
    • Specifying when subjects exit from the analysis
    • Specifying when subjects enter the analysis
    • Specifying the subject ID variable
    • Handling gaps
• After (st) setting your data
  • Look at stset's output
  • Use stdescribe
  • Use stvary
  • Perhaps use stfill
• Example: Hip fracture data
• Appendices
  • Dates
  • Other formats
  • Convenience options

• Nonparametric estimation
• The Kaplan–Meier product-limit estimator of the survivor curve
  • Calculation of the Kaplan–Meier survivor curve
  • Censored observations
  • Delayed entry
  • Gaps
  • Properties of the Kaplan–Meier estimator
  • The sts graph command
  • The sts list command
  • The stsum command
• The Nelson–Aalen estimator of the cumulative hazard
• Alternative estimators of the survivor and cumulative hazard functions
• Comparing survival experience
  • The log-rank test
  • The Wilcoxon test
  • The Tarone–Ware test
  • The Peto–Peto–Prentice test
  • The Fleming–Harrington test
  • Test for trend across ordered groups
  • The Cox test

Course leaders are available for discussion during the break.

• Introduction
• The Cox model has no intercept
• Interpreting coefficients
• The effect of units on coefficients
• The baseline hazard and related functions
• The effect of units on the baseline functions
• Summary of stcox command
• The calculation of results
• No tied failures
• Tied failures
  • The marginal calculation
  • The partial calculation
  • The Breslow approximation
  • The Efron approximation
  • Summary
• Stratified analysis
• Obtaining coefficient estimates
• Obtaining the baseline functions
• Modeling
• Indicator variables
• Categorical variables
• Continuous variables
• Interactions
• Time-varying variables
  • Using stcox with option tvc()
  • Using stsplit
• Testing the proportional-hazards assumption
• Tests based on reestimation
• Test based on Schoenfeld residuals
• Graphical methods
• Residuals
  • Determining functional form
  • Assessing goodness of fit
  • Finding outliers and influential points

• Introduction
• Classes of parametric models
  • Parametric proportional-hazards models
  • Accelerated failure-time models
• Maximum likelihood estimation for parametric models
• A survey of parametric regression models in Stata
  • Exponential regression
    • Exponential regression in the PH formulation
    • Exponential regression in the AFT formulation
  • Weibull regression
    • Weibull regression in the PH formulation
    • Weibull regression in the AFT formulation
  • Gompertz regression (PH formulation)
  • Lognormal regression (AFT formulation)
  • Loglogistic regression (AFT formulation)
  • Generalized log-gamma regression (AFT formulation)
• Choosing among parametric models
  • Nested models
  • Nonnested models
• Stratified models
• Use of predict after streg
  • Predicting time of failure
  • Predicting the hazard and related functions
  • Calculating residuals
• Use of stcurve after streg