Sign Test
Performs one- and two-sample sign tests on vectors of data.
SignTest(x, ...)
## Default S3 method:
SignTest(x, y = NULL, alternative = c("two.sided", "less", "greater"),
mu = 0, conf.level = 0.95, ... )
## S3 method for class 'formula'
SignTest(formula, data, subset, na.action, ...)x |
numeric vector of data values. Non-finite (e.g. infinite or missing) values will be omitted. |
y |
an optional numeric vector of data values: as with x non-finite values will be omitted. |
mu |
a number specifying an optional parameter used to form the null hypothesis. See Details. |
alternative |
is a character string, one of |
conf.level |
confidence level for the returned confidence interval, restricted to lie between zero and one. |
formula |
a formula of the form |
data |
an optional matrix or data frame (or similar: see |
subset |
an optional vector specifying a subset of observations to be used. |
na.action |
a function which indicates what should happen when the data contain NAs. Defaults to |
... |
further arguments to be passed to or from methods. |
The formula interface is only applicable for the 2-sample test.
SignTest computes a “Dependent-samples Sign-Test” if both
x and y are provided. If only x is provided,
the “One-sample Sign-Test” will be computed.
For the one-sample sign-test, the null hypothesis is
that the median of the population from which x is drawn is mu.
For the two-sample dependent case, the null hypothesis is
that the median for the differences of the populations from which x
and y are drawn is mu.
The alternative hypothesis indicates the direction of divergence of the
population median for x from mu (i.e., "greater",
"less", "two.sided".)
The confidence levels are exact.
A list of class htest, containing the following components:
statistic |
the S-statistic (the number of positive differences between the data and the hypothesized median), with names attribute “S”. |
parameter |
the total number of valid differences. |
p.value |
the p-value for the test. |
null.value |
is the value of the median specified by the null hypothesis. This
equals the input argument |
alternative |
a character string describing the alternative hypothesis. |
method |
the type of test applied. |
data.name |
a character string giving the names of the data. |
conf.int |
a confidence interval for the median. |
estimate |
the sample median. |
Andri Signorell <andri@signorell.net>
Gibbons, J.D. and Chakraborti, S. (1992): Nonparametric Statistical Inference. Marcel Dekker Inc., New York.
Kitchens, L. J. (2003): Basic Statistics and Data Analysis. Duxbury.
Conover, W. J. (1980): Practical Nonparametric Statistics, 2nd ed. Wiley, New York.
t.test, wilcox.test, ZTest, binom.test,
SIGN.test in the package BSDA (reporting approximative confidence intervals).
x <- c(1.83, 0.50, 1.62, 2.48, 1.68, 1.88, 1.55, 3.06, 1.30) y <- c(0.878, 0.647, 0.598, 2.05, 1.06, 1.29, 1.06, 3.14, 1.29) SignTest(x, y) wilcox.test(x, y, paired = TRUE) d.light <- data.frame( black = c(25.85,28.84,32.05,25.74,20.89,41.05,25.01,24.96,27.47), white <- c(18.23,20.84,22.96,19.68,19.5,24.98,16.61,16.07,24.59), d <- c(7.62,8,9.09,6.06,1.39,16.07,8.4,8.89,2.88) ) d <- d.light$d SignTest(x=d, mu = 4) wilcox.test(x=d, mu = 4, conf.int = TRUE) SignTest(x=d, mu = 4, alternative="less") wilcox.test(x=d, mu = 4, conf.int = TRUE, alternative="less") SignTest(x=d, mu = 4, alternative="greater") wilcox.test(x=d, mu = 4, conf.int = TRUE, alternative="greater") # test die interfaces x <- runif(10) y <- runif(10) g <- rep(1:2, each=10) xx <- c(x, y) SignTest(x ~ group, data=data.frame(x=xx, group=g )) SignTest(xx ~ g) SignTest(x, y) SignTest(x - y)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.