TwoSampleKaplanMeier function

Risk difference and risk ratio using the Kaplan-Meier method

Computes a risk difference, risk ratio or survival ratio with right-censored data, together with a confidence interval and a p-value (to test for a difference between two groups). Pointwise estimates are computed via the Kaplan-Meier estimator. Computation of confidence intervals and p-values are based on either Empirical Likelihood (EL) inference or Wald-type inference. Both are non-parametric approaches, which are asymptotically equivalent. See Thomas & Grunkemeier (1975) for details about the Empirical Likelihood method. For the Wald-type approach, the asymptotic normal approximation is used on the log scale for the risk ratio or survival ratio. No transformation is used for the risk or survival difference.

TwoSampleKaplanMeier(
  time,
  status,
  group,
  t,
  SR.H0 = 1,
  RR.H0 = 1,
  Diff.H0 = 0,
  level = 0.95,
  contr = list(tol = 1e-05, algo = 2, k = 3, Trace = FALSE, method = "both")
)

Arguments

• time: vector of times (possibly censored)
• status: vector of usual survival status indicators (0 for censored observations, 1 otherwise)
• group: vector of binary group indicator. The reference group should be coded 0, the other 1.
• t: the time point of interest (e.g. 1 to compute 1-year risk ratio)
• SR.H0: the survival ratio under the null hypothesis, to compute a p-value. Default is 1.
• RR.H0: the risk ratio under the null hypothesis, to compute a p-value. Default is 1.
• Diff.H0: the risk difference under the null hypothesis, to compute a p-value. Default is 0.
• level: confidence level for the confidence intervals. Default is 0.95.
• contr: list of control parameters. tol=tolerance for numerical computation, default is 1e-5. method="EL", "Wald" or "both" indicates wether 95% CI and the p-value should be computed based on Empirical Likelihood inference, Wald-type inference or both. algo=2 is currently the only option that is implemented.

Returns

an object of class 'TwoSampleKaplanMeier'

Examples

# This example reproduces some results presented in Table 4 of Thomas and Grunkemeier (1975)
Res2SKM95 <- TwoSampleKaplanMeier(time=Freireich$time,
                                  status=Freireich$status,
                                  group=Freireich$group,
                                  t=10)
Res2SKM95

References

Thomas & Grunkemeier (1975). Confidence interval estimation of survival probabilities for censored data. Journal of the American Statistical Association, 70(352), 865-871.

Author(s)

Paul Blanche