STAND (version 2.0)

kmms: Kaplan-Meier (KM) Mean and Standard Error

Description

Kaplan- Meier Estimate of Mean and Standard Error of the Mean for Left Censored Data

Usage

kmms(dd, gam = 0.95)

Arguments

dd
An n by 2 matrix or data frame with x (exposure) variable in column 1, and det= 0 for non-detect or 1 for detect in column 2
gam
one-sided confidence level $\gamma$. Default is 0.95

Value

A LIST with components:
KM.mean
Kaplan- Meier(KM) estimate of mean E(X)
KM.LCL
KM estimate of lower confidence limit
KM.UCL
KM estimate of upper confidence limit
KM.se
estimate of standard error of KM-mean
gamma
one-sided confidence level $\gamma$. Default 0.95

Details

The product limit estimate (PLE) of the cumulative distribution function was first proposed by Kaplan and Meier (1958) for right censored data. Turnbull (1976) provides a more general treatment of nonparametric estimation of the distribution function for arbitrary censoring. For randomly left censored data, the PLE is defined by Schmoyer et al. (1996)--see plend.

The mean of the PLE is a censoring-adjusted point estimate of E(X) the mean of X. An approximate standard error of the PLE mean can be obtained using the method of Kaplan and Meier (1958), and the $100\gamma\%$ UCL is $KM.mean + t(\gamma -1, m-1) sp$, where sp is the Kaplan-Meier standard error of the mean adjusted by the factor $m/(m-1)$, where m is the number of detects in the sample. When there is no censoring this reduces to the second approximate method described by Land (1972).

References

Kaplan, E. L. and Meier, P. (1958), "Nonparametric Estimation from Incomplete Observations," Journal of the American Statistical Association, 457-481.

Schmoyer, R. L., J. J. Beauchamp, C. C. Brandt and F. O. Hoffman, Jr. (1996), "Difficulties with the Lognormal Model in Mean Estimation and Testing," Environmental and Ecological Statistics, 3, 81-97.

See Also

plend, plekm

Examples

Run this code
# results for beTWA data using kmms in stand Ver 1.1 with error
#    KM.mean      KM.LCL      KM.UCL       KM.se       gamma 
# 0.018626709 0.014085780 0.023167637 0.002720092 0.950000000
#
data(beTWA) # Use data from Example 2 in ORNLTM2002-51
unlist(kmms(beTWA))

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