summary.coxph_mpl function

Summarise a coxph_mpl Object

Additional information about the Cox proportional hazard model fit represented by object is extracted and included in the returned object, which is suitable for printing with the generic print function. The generic coef function will extract the matrix of coefficients of interest with standard errors, $z$-statistics and $p$-values. See coef.summary.coxph_mpl.

Only the baseline hazard parameters larger than min.Theta (see coxph_mpl.control) are reported. utf8

## S3 method for class 'coxph_mpl'
summary(object, se="M2QM2", full=FALSE, ...)

## S3 method for class 'summary.coxph_mpl'
print(x, se="M2QM2", ...)

Arguments

• object: In an object inheriting from class coxph_mpl, representing a fitted Cox proportional hazard model.
• se: an inference method. Possibilites are "H", "M2QM2" and "M2HM2". Refer to the Details Section of coxph_mpl. Default is se="M2QM2".
• full: logical. If TRUE inference for the baseline hasard parameters is provided. Default is full=FALSE.
• x: an object inheriting from class summary.coxph_mpl, representing the summary of a fitted Cox proportional hazard model.
• ...: Other arguments passed through to printing functions.

Returns

an object of class summary.coxph_mpl representing the fit and additional information. - Beta: a matrix of $p$ rows indicating the regression parameter estimates, standard errors, z-statistics values and according p-values.

• Theta: If full == TRUE, a matrix of $m$ rows indicating the baseline hazard parameter estimates, standard errors, z-statistics values and according p-values. If full == FALSE, the baseline hazard estimates.

• inf: a list of elements extracted from the object of class coxph_mpl

  including the number of iterations and the penalised likelihood value, for example.

See Also

coxph_mpl, coxph_mpl.control, coxph_mpl.object and plot.coxph_mpl.

Author(s)

Dominique-Laurent Couturier, Maurizio Manuguerra

Examples

## Not run:

data(lung)

fit_mpl <- coxph_mpl(Surv(time, status == 2) ~ age + sex + ph.karno + wt.loss, data = lung)

summary(fit_mpl, full = TRUE)
summary(fit_mpl, se = "M2HM2")
## End(Not run)