NormalMeanDiffCens: Maximum Likelihood Estimator for the mean difference between...

Description Usage Arguments Value Author(s) References Examples

View source: R/NormalMeanDiffCens.R

Description

Computes estimates of the parameters of two censored Normal samples, as well as the mean difference between the two samples.

Usage

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NormalMeanDiffCens(censdata1, censdata2, conf.level = 0.95, 
     null.values = c(0, 0, 1, 1))

Arguments

censdata1

Observations of first sample, format as specified by code = interval2 in Surv.

censdata2

Observations of second sample, as specified by code = interval2 in Surv.

conf.level

Confidence level for confidence intervals.

null.values

Fixed values for hypothesis tests. Four-dimensional vector specifying the hypothesis for μ_1, μ_2, σ_1, σ_2.

Value

A table with estimators and inference for the means and standard deviations of both samples, as well as the difference Δ between the mean of the first and second sample. Hypothesis tests are for the values in null.values and for the null hypothesis of no mean difference.

Author(s)

Stanislas Hubeaux, [email protected]

Kaspar Rufibach, [email protected]
http://www.kasparrufibach.ch

References

Hubeaux, S. (2013). Estimation from left- and/or interval-censored samples. Technical report, Biostatistics Oncology, F. Hoffmann-La Roche Ltd.

Lynn, H. S. (2001). Maximum likelihood inference for left-censored HIV RNA data. Stat. Med., 20, 33–45.

Examples

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## example with interval-censored Normal samples
n <- 500
prop.cens <- 0.35
mu <- c(0, 2)
sigma <- c(1, 1)

set.seed(2013)

## Sample 1:
LOD1 <- qnorm(prop.cens, mean = mu[1], sd = sigma[1])
x1 <- rnorm(n, mean = mu[1], sd = sigma[1])
s1 <- censorContVar(x1, LLOD = LOD1)

## Sample 2:
LOD2 <- qnorm(0.35, mean = mu[2], sd = sigma[2])
x2 <- rnorm(n, mean = mu[2], sd = sigma[2])
s2 <- censorContVar(x2, LLOD = LOD2)

## inference on distribution parameters and mean difference:
NormalMeanDiffCens(censdata1 = s1, censdata2 = s2)

SurvRegCensCov documentation built on May 30, 2017, 3:32 a.m.