View source: R/NormalMeanDiffCens.R
NormalMeanDiffCens | R Documentation |
Computes estimates of the parameters of two censored Normal samples, as well as the mean difference between the two samples.
NormalMeanDiffCens(censdata1, censdata2, conf.level = 0.95,
null.values = c(0, 0, 1, 1))
censdata1 |
Observations of first sample, format as specified by |
censdata2 |
Observations of second sample, as specified by |
conf.level |
Confidence level for confidence intervals. |
null.values |
Fixed values for hypothesis tests. Four-dimensional vector specifying the hypothesis for |
A table with estimators and inference for the means and standard deviations of both samples, as well as the difference \Delta
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.
Stanislas Hubeaux, stan.hubeaux@bluewin.ch
Kaspar Rufibach, kaspar.rufibach@gmail.com
http://www.kasparrufibach.ch
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.
## 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)
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