smoothSurv (version 1.6)

print.smoothSurvReg: Summary and Print for Objects of Class 'smoothSurvReg'

Description

Print a summary information of the fitted model.

For regression coefficients the following information is given:

Value	-
estimate of the coefficient	Std.Error
-	estimated standard error based on the pseudo-variance estimate (3.1)
in Komárek, Lesaffre and Hilton (2005)	Std.Error2
-	estimated standard error based on the asymptotic variance estimate (3.2)
in Komárek, Lesaffre and Hilton (2005)	Z
-	the Wald statistic obtained as Value divided by Std.Error
Z2	-
the Wald statistic obtained as Value divided by Std.Error2	p
-	the two-sided P-value based on normality of the statistic Z
p2	-
the two-sided P-value based on normality of the statistic Z2	Value

Further, we print:

Lambda	-
the optimal value of the smoothing hyperparameter
	divided by the sample size, i.e., $lambda/n$ in the notation
of Komárek, Lesaffre and Hilton (2005)	Log(Lambda)
-	logarithm of the above
df	-
effective degrees of freedom of the model, see Section 2.2.3
	of Komárek, Lesaffre and Hilton (2005)
AIC	-
Akaike's information criterion of the model, see Section 2.2.3
	of Komárek, Lesaffre and Hilton (2005)

With argument spline set to TRUE, analogous table like that for the regression coefficients is printed also for the weights of the penalized Gaussian mixture (G-spline).

Usage

"print"(x, spline, digits = min(options()$digits, 4), ...)
"summary"(object, spline, digits = min(options()$digits, 4), ...)

Arguments

x

Object of class smoothSurvReg.

object

Object of class smoothSurvReg.

spline

TRUE/FALSE. If TRUE an information on fitted G-spline is printed.

digits

Controls the number of digits to print when printing numeric values. It is a suggestion only. Valid values are 1...22.

...

Further arguments passed to or from other methods.

References

Komárek, A., Lesaffre, E., and Hilton, J. F. (2005). Accelerated failure time model for arbitrarily censored data with smoothed error distribution. Journal of Computational and Graphical Statistics, 14, 726--745.

Lesaffre, E., Komárek, A., and Declerck, D. (2005). An overview of methods for interval-censored data with an emphasis on applications in dentistry. Statistical Methods in Medical Research, 14, 539--552.

See Also

smoothSurvReg, print, summary