Computes the runs test for randomness of the dichotomous (binary) data
runs.test(x, alternative = c("two.sided", "less", "greater"))
- a dichotomous factor.
- indicates the alternative hypothesis and must be
"greater". You can specify just the initial letter.
This test searches for randomness in the observed data series
x by examining the frequency of runs. A "run" is defined as a
series of similar responses.
Note, that by using the alternative
"less" the null of
randomness is tested against some kind of "under-mixing"
("trend"). By using the alternative
"greater" the null of
randomness is tested against some kind of "over-mixing"
Missing values are not allowed.
- A list with class
"htest"containing the following components:
statistic the value of the test statistic. p.value the p-value of the test. method a character string indicating what type of test was performed. data.name a character string giving the name of the data. alternative a character string describing the alternative hypothesis.
S. Siegel (1956): Nonparametric Statistics for the Behavioural Sciences, McGraw-Hill, New York. S. Siegel and N. J. Castellan (1988): Nonparametric Statistics for the Behavioural Sciences, 2nd edn, McGraw-Hill, New York.
x <- factor(sign(rnorm(100))) # randomness runs.test(x) x <- factor(rep(c(-1,1),50)) # over-mixing runs.test(x)