NADA: cenfit – R documentation

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cenfit

Compute an ECDF for Censored Data

Description

Computes an estimate of an empirical cumulative distribution function (ECDF) for censored data using the Kaplan-Meier method.

Usage

cenfit(obs, censored, groups, ...)

Arguments

`obs`	Either a numeric vector of observations or a formula. See examples below.
`censored`	A logical vector indicating TRUE where an observation in ‘obs’ is censored (a less-than value) and FALSE otherwise.
`groups`	A factor vector used for grouping ‘obs’ into subsets.
`...`	Additional items that are common to this function and the `survfit` function from the ‘survival’ package. See Details.

Details

This, and related routines, are front ends to routines in the survival package. Since the survival routines can not handle left-censored data, these routines transparently handle “flipping" input data and resultant calculations. Additionally provided are query and prediction methods for cenfit objects.

There are many additional options that are supported and documented in survfit. Only a few have application to the geosciences. However, the most important is ‘conf.int’. This is the level for a two-sided confidence interval on the ECDF. The default is 0.95.

If you are using the formula interface: The censored and groups parameters are not specified – all information is provided via a formula as the obs parameter. The formula must have a Cen object as the response on the left of the ~ operator and, if desired, terms separated by + operators on the right.

Value

a cenfit object. Methods defined for cenfit objects are provided for print, plot, lines, predict, mean, median, sd, quantile.

If the input formula contained factoring groups (ie., cenfit(obs, censored, groups), individual ECDFs can be obtained by indexing (eg., model[1], etc.).

Author(s)

R. Lopaka Lee <rclee@usgs.gov>

Dennis Helsel <dhelsel@practicalstats.com>

References

Helsel, Dennis R. (2005). Nondectects and Data Analysis; Statistics for censored environmental data. John Wiley and Sons, USA, NJ.

Dorey, F. J. and Korn, E. L. (1987). Effective sample sizes for confidence intervals for survival probabilities. Statistics in Medicine 6, 679-87.

Fleming, T. H. and Harrington, D.P. (1984). Nonparametric estimation of the survival distribution in censored data. Comm. in Statistics 13, 2469-86.

Kalbfleisch, J. D. and Prentice, R. L. (1980). The Statistical Analysis of Failure Time Data. Wiley, New York.

Link, C. L. (1984). Confidence intervals for the survival function using Cox's proportional hazards model with covariates. Biometrics 40, 601-610.

Examples

# Create a Kaplan-Meier ECDF, plot and summarize it.

    data(Cadmium)

    obs      = Cadmium$Cd
    censored = Cadmium$CdCen

    mycenfit = cenfit(obs, censored) 

    plot(mycenfit)
    summary(mycenfit)
    quantile(mycenfit, conf.int=TRUE)
    median(mycenfit)
    mean(mycenfit)
    sd(mycenfit)
    predict(mycenfit, c(10, 20, 100), conf.int=TRUE)

    # With groups
    groups = Cadmium$Region

    cenfit(obs, censored, groups)
    
    # Formula interface -- no groups
    cenfit(Cen(obs, censored)) 

    # Formula interface -- with groups
    cenfit(Cen(obs, censored)~groups)

NADA

Nondetects and Data Analysis for Environmental Data

v1.6-1.1

GPL (>= 2)

Authors

Lopaka Lee

Initial release