invGauss (version 1.2)

summary.invGauss: Summarize the estimation result from invGauss

Description

To be used on a result from invGauss. The summary function provides estimates, standard errors etc.

Usage

# S3 method for invGauss
summary(object, covariance = FALSE, ...)

Arguments

object

Result from running invGauss.

covariance

Logical, indicates whether the asymptotic variance-covariance matrix for the parameter estimates should be returned.

...

Other arguments (ignored).

Value

Returns a list with the most important results from invGauss, including coefficients with standard errors and Wald tests:

coefficients:

Estimated coefficients, with standard errors and Wald tests

cov.unscaled:

The variance-covariance matrix of the estimated coefficients

loglik:

The maximized log-likelihood

AIC:

AIC value

Details

See web page http://www.uib.no/smis/gjessing/projects/invgauss/ for more details.

References

Aalen OO, Borgan O, Gjessing HK. Survival and Event History Analysis: A Process Point of View. Springer-Verlag, 2008. Aalen OO and Gjessing HK. Understanding the Shape of the Hazard Rate: A Process Point of View. Statistical Science, 2001, Vol. 1, No. 1, 1-22. Aalen OO. Phase type distributions in survival analysis. Scandinavian Journal of Statistics, 1995, Vol. 22, Issue 4, 447-463. Web Site: http://www.uib.no/smis/gjessing/projects/invgauss/

See Also

invGauss

Examples

# NOT RUN {
<!-- %\dontrun{ -->
# }
# NOT RUN {
# Simple run:
data(d.oropha.rec)
res <- invGauss(formula.mu = Surv(time, status) ~ 1, data = d.oropha.rec)
summary(res)

# Use covariates for c, with exponential link function
data(d.oropha.rec)
res <- invGauss(formula.mu = Surv(time, status) ~ 1, formula.c = ~ cond + nstage + tstage, 
data = d.oropha.rec) # MODEL 5 (TABLE 10.2) IN SPRINGER BOOK
summary(res)
# }
# NOT RUN {
<!-- %} -->
# }