overdispersionCheck {evidence}

A robust comparison of the location and the scale of the input vector.

Description

A large sample of Normal-distributed data with more than 10% of the observations further than 1.5 times the IQR from the median shows signs of overdispersion, as recommended in Gelman et al., 2014.

Usage

overdispersionCheck(x)

Arguments

x

an input vector of reals without missing values

Value

The function prints the approximate percentage of observations that are further from the median than would be expected in a normal distribution.

Author(s)

Robert van Hulst

References

Gelman, A., Carlin, J.B., Stern, H.S., Dunson, D.B., Vehtari, A., and Rubin, D.B. 2014. Bayesian Data Analysis. Third Ed.. CRC Press

Examples

overdispersionCheck(rt(100, 1))