bimodality_coefficient {mousetrap} | R Documentation |
Calculate bimodality coefficient.
Description
Calculate the bimodality coefficient for a numeric vector as specified in Pfister et al. (2013).
Usage
bimodality_coefficient(x, na.rm = FALSE)
Arguments
x |
a numeric vector. |
na.rm |
logical specifying whether missing values should be removed. |
Details
The calculation of the bimodality coefficient involves calculating the
skewness and kurtosis of the distribution first. For this, the
skew and kurtosi functions of the psych
package are used.
Note that type is set to "2" for these functions in accordance with
Pfister et al. (2013).
Value
A numeric value.
Author(s)
Pascal J. Kieslich
Felix Henninger
References
Pfister, R., Schwarz, K. A., Janczyk, M., Dale, R., & Freeman, J. B. (2013). Good things peak in pairs: A note on the bimodality coefficient. Frontiers in Psychology, 4, 700. doi:10.3389/fpsyg.2013.00700
See Also
skew for calculating skewness and kurtosis.
mt_check_bimodality for assessing bimodality using several methods in a mousetrap data object.
Examples
pfister_data_a <- rep(1:11, times=c(3,5,5,10,17,20,17,10,5,5,3))
bimodality_coefficient(pfister_data_a) #.34
pfister_data_b <- rep(1:11, times=c(2,26,14,6,2,0,2,6,14,26,2))
bimodality_coefficient(pfister_data_b) #.79