ScoreTest: Do a score test under the proportional hazards model for...

In glrt: Generalized Logrank Tests for Interval-censored Failure Time Data

Description

The ScoreTest function conducts a k(>=2)-sample test for interval-censored survival data. The test is based on Finkelstein (1986). The null hypothesis is that all k survival functions of the failure time are the same, and the alternative hypothesis is that not all functions are the same. It is not referred as gLRT4 as in Zhao (2012).

Usage

ScoreTest(A, k = 2, EMstep = TRUE, ICMstep = TRUE, tol = 1e-06, 
maxiter = 1000, inf = Inf)

Arguments

A	an n by 3 data matrix with the censoring interval of the format (L, R] in columns 1 & 2 and treatmentment indicator ranging from 0 to k-1 in column 3.
k	number of treatments. The default is 2.
EMstep	a boolean variable indicating whether to take an EM step in the iteration when estimating the common distribution function. The default is TRUE.
ICMstep	a boolean variable indicating whether to take an ICM step in the iteration when estimating the common distribution function. The default is TRUE.
tol	the maximal L_1 distance between successive estimates before stopping iteration when estimating the common distribution function. The default is 1.0e-6.
maxiter	the maximal number of iterations to perform before stopping when estimating the common distribution function. The default is 1000.
inf	value used in data for infinity. The default is Inf.

Details

Under the null hypothesis that k survival functions are the same, the NPMLE of the common survival function is computed by function ModifiedEMICM.

The chi-square test in ScoreTest has k-1 degrees of freedom.

Value

The function returns an object containing the following components:

method	test procedure used
u	the test statistic
v	the estimated covariance of the test statistic
chisq	the chisquare test statistic
df	the degrees of freedom of the test
p	p-value of the test

Author(s)

Qiang Zhao and Jianguo Sun

References

Finkelstein, DM (1986), "A Proportional Hazards Model for Interval-censored Failure Time Data", Biometrics, 42: 845-854.

Q. Zhao (2012), "gLRT - A New R Package for Analyzing Interval-censored Survival Data", Interval-Censored Time-to-Event Data: Methods and Applications, CRC Press, 377-396.

See Also

ModifiedEMICM, gLRT, gLRT1, gLRT2, gLRT3, gLRT4

Examples

data(cosmesis)
ScoreTest(cosmesis, inf=100)

data(diabetes)
ScoreTest(diabetes)

Example output

Loading required package: survival
$method
[1] "Score Test under the proportional hazards model (Finkelstein, 1986)"

$u
[1] -9.944188  9.944178

$var
          [,1]      [,2]
[1,]  10.65337 -10.65337
[2,] -10.65337  10.65337

$chisq
         [,1]
[1,] 9.282218

$df
[1] 1

$p
           [,1]
[1,] 0.00231389

attr(,"row.names")
integer(0)
attr(,"class")
[1] "Score Test"
$method
[1] "Score Test under the proportional hazards model (Finkelstein, 1986)"

$u
[1]  22.5003 -22.5003

$var
          [,1]      [,2]
[1,]  157.4278 -157.4278
[2,] -157.4278  157.4278

$chisq
         [,1]
[1,] 3.215845

$df
[1] 1

$p
           [,1]
[1,] 0.07292852

attr(,"row.names")
integer(0)
attr(,"class")
[1] "Score Test"

glrt documentation built on May 2, 2019, 8:31 a.m.