NADA (version 1.6-1.2)

cendiff: Test Censored ECDF Differences

Description

Tests if there is a difference between two or more empirical cumulative distribution functions (ECDF) using the \(G^\rho\) family of tests, or for a single curve against a known alternative.

Usage

cendiff(obs, censored, groups, ...)

Value

Returns a list with the following components:

n

the number of subjects in each group.

obs

the weighted observed number of events in each group. If there are strata, this will be a matrix with one column per stratum.

exp

the weighted expected number of events in each group. If there are strata, this will be a matrix with one column per stratum.

chisq

the chisquare statistic for a test of equality.

var

the variance matrix of the test.

strata

optionally, the number of subjects contained in each stratum.

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 survdiff function from the `survival' package. See Details.

Author

R. Lopaka Lee <[e-mail]>

Dennis Helsel <[e-mail]>

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.

This function shares the same arguments as survdiff. The most important of which is rho which controls the type of test. With rho = 0 this is the log-rank or Mantel-Haenszel test, and with rho = 1 it is equivalent to the Peto & Peto modification of the Gehan-Wilcoxon test. The default is rho = 1, or the Peto & Peto test. This is the most appropriate for left-censored log-normal data.

For the formula interface: if the right hand side of the formula consists only of an offset term, then a one sample test is done. To cause missing values in the predictors to be treated as a separate group, rather than being omitted, use the factor function with its exclude argument.

References

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

Harrington, D. P. and Fleming, T. R. (1982). A class of rank test procedures for censored survival data. Biometrika 69, 553-566.

See Also

Cen, survdiff

Examples

    data(Cadmium)

    obs      = Cadmium$Cd
    censored = Cadmium$CdCen
    groups   = Cadmium$Region

    # Cd differences between regions?
    cendiff(obs, censored, groups)
    
    # Same as above using formula interface
    cenfit(Cen(obs, censored)~groups)