summary.invGauss function

Summarize the estimation result from invGauss

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

## S3 method for class '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).

Details

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

Returns

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

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/

Author(s)

Hakon K. Gjessing

Professor of Biostatistics

Division of Epidemiology

Norwegian Institute of Public Health

[email protected]

http://www.uib.no/smis/gjessing

Note

Further information is found on the web page

See Also

invGauss

Examples

# 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)