lrt {clikcorr}

censoring data and likelihood-based correlation estimation inference

Description

Provides likelihood ratio tests for making statistical inference about the correlation coefficient from bivariate censored/missing data.

Usage

lrt(data, lower1, upper1, lower2, upper2, dist = "n", df = 4, 
 sv = NA, r0 = 0, nlm = FALSE, ...)

Arguments

data

a data frame name.

lower1

the lower bound of the first of the two variables whose correlation coefficient to be calculated.

upper1

the upper bound of the first of the two variables whose correlation coefficient to be calculated.

lower2

the lower bound of the second of the two variables whose correlation coefficient to be calculated.

upper2

the upper bound of the second of the two variables whose correlation coefficient to be calculated.

dist

working distribution. By default, dist="n" assuming the data from a bivariate normal distribution. Set dist="t" if the data are assumed generated from a bivariate t-distribution.

df

degree of freedom of the bivariate t-distribution when dist="t". By default df=4.

sv

user specified starting values for the vector of (mean1, mean2, var1, corr, var2).

r0

correlation coefficient value under the null hypothesis. By default is 0.

nlm

use nlm as the optimization method to minimize the negative log (profile) likelihood. By default nlm=FALSE and optim is used to maximize the log (profile) likelihood.

...

not used.

Value

Cor

maximum likelihood estimate (MLE) of the correlation coefficient.

m1llk

value of the log likelihood function evaluated at the MLE.

m0llk

value of the log likelihood function evaluated at the r0.

P0

p-value for likelihood ratio test with null hypothesis says that the true correlation coefficient equals r0.

Author(s)

Yanming Li, Kerby Shedden, Brenda W. Gillespie and John A. Gillespie.

References

Yanming Li, Kerby Shedden, Brenda W. Gillespie and John A. Gillespie (2016). Calculating Profile Likelihood Estimates of the Correlation Coefficient in the Presence of Left, Right or Interval Censoring and Missing Data.

Examples

data(ND)
logND <- log(ND)

lrt(logND, "t1_TCDD", "t2_TCDD", "t1_PeCDD", "t2_PeCDD")

## Not run: 
lrt(logND, "t1_TCDD", "t2_TCDD", "t1_PeCDD", "t2_PeCDD", dist="t")

## End(Not run)