runtest tests whether the observations of x are serially independent i.e. whether they occur in a random order, by counting how many runs there are above and below a threshold. By default, the median is used as the threshold. A small number of runs indicates positive serial correlation; a large number indicates negative serial correlation.

ifr_runs_test(
data,
x,
drop = FALSE,
split = FALSE,
mean = FALSE,
threshold = NA
)

## Arguments

data a data.frame or tibble numeric; column in data logical; if TRUE, values equal to the threshold will be dropped from x logical; if TRUE, data will be recoded in binary format logical; if TRUE, mean will be used as threshold threshold to be used for counting runs, specify 0 if data is coded as a binary.

## Value

ifr_runs_test returns an object of class "ifr_runs_test". An object of class "ifr_runs_test" is a list containing the following components:

n

number of observations

threshold

within group sum of squares

n_below

number below the threshold

n_above

number above the threshold

mean

expected number of runs

var

variance of the number of runs

n_runs

number of runs

z

z statistic

p

p-value of z

## Deprecated Function

runs_test() has been deprecated. Instead use ifr_runs_test().

Sheskin, D. J. 2007. Handbook of Parametric and Nonparametric Statistical Procedures, 4th edition. : Chapman & Hall/CRC.

Edgington, E. S. 1961. Probability table for number of runs of signs of first differences in ordered series. Journal of the American Statistical Association 56: 156–159.

Madansky, A. 1988. Prescriptions for Working Statisticians. New York: Springer.

Swed, F. S., and C. Eisenhart. 1943. Tables for testing randomness of grouping in a sequence of alternatives. Annals of Mathematical Statistics 14: 66–87.

## Examples

ifr_runs_test(hsb, read)
#> Runs Test
#>  Total Cases:  200
#>  Test Value :  50
#>  Cases < Test Value:  101
#>  Cases > Test Value:  99
#>  Number of Runs:  95
#>  Expected Runs:  100.99
#>  Variance (Runs):  49.73874
#>  z Statistic:  -0.8493358
#>  p-value:  0.3956945

#> Runs Test
#>  Total Cases:  200
#>  Test Value :  50
#>  Cases < Test Value:  83
#>  Cases > Test Value:  99
#>  Number of Runs:  89
#>  Expected Runs:  91.2967
#>  Variance (Runs):  44.54805
#>  z Statistic:  -0.3441046
#>  p-value:  0.7307676

#> Runs Test
#>  Total Cases:  200
#>  Test Value :  50
#>  Cases < Test Value:  101
#>  Cases > Test Value:  99
#>  Number of Runs:  95
#>  Expected Runs:  100.99
#>  Variance (Runs):  49.73874
#>  z Statistic:  -0.8493358
#>  p-value:  0.3956945

#> Runs Test
#>  Total Cases:  200
#>  Test Value :  52.23
#>  Cases < Test Value:  115
#>  Cases > Test Value:  85
#>  Number of Runs:  93
#>  Expected Runs:  98.75
#>  Variance (Runs):  47.52418
#>  z Statistic:  -0.8340854
#>  p-value:  0.4042329