km: Kaplan-Meier survivorship.

In asbio: A Collection of Statistical Tools for Biologists

Kaplan-Meier survivorship.

Description

Calculates survivorship for individuals in a population over time based on the method of Kaplan-Meier; cf. Pollock et al. (1989).

Usage

km(r, d, var = "O", conf = 0.95, age.seq=seq(1,length(r)),
ylab = "Survivorship", xlab = "Age class", type = "b", 
plot.km = TRUE, plot.CI = TRUE, ...)

Arguments

r	Numbers of individuals at risk in each age or time class.
d	Vector of the number of deaths in each age or time class.
var	Type of procedure used to calculate variance in confidence intervals "O" = Oakes, "G" = Greenwood.
conf	Level of confidence for confidence interval calculations; 1 - P(type I error)
age.seq	A sequence of numbers indicating the age classes used.
ylab	Y-axis label.
xlab	X-axis label.
type	type argument from plot.
plot.km	Logical. Should plot be created?
plot.CI	Logical. Should confidence interval be overlaid on plot?
...	Additional arguments from plot.

Details

Details for this index are given in Pollock et al. (1989).

Value

Returns a list with the following components

s.hat	A vector of estimated survivorship probabilities from the 1st age class onward.
Greenwood.Var	The estimated Greenwood variance for each age class.
Oakes.Var	The estimated Oakes variance for each age class.
CI	Upper and lower confidence bound to the true survivorship.

Author(s)

Ken Aho

References

Pollock, K. H., Winterstein, S. R., and Curtis, P. D. (1989) Survival analysis in telemetry studies: the staggered entry design. Journal of Wildlife Management. 53(1):7-1.

Examples

##Example from Pollock (1989)
r<-c(18,18,18,16,16,16,15,15,13,10,8,8,7)
d<-c(0,0,2,0,0,1,0,1,1,1,0,0,0)

km(r,d)

asbio documentation built on Aug. 20, 2023, 9:07 a.m.