Assess for observations with reported z-statistic z and a signficand of s for the standard error whether it is at risk of the errors: misclassification, wrong inclusion, wrong exclusion

Assess for observations with reported z-statistic z and a signficand of s for the standard error whether it is at risk of the errors: misclassification, wrong inclusion, wrong exclusion

rounding.risks(z, s, z0 = 1.96, h = 0.2)

Arguments

z	a vector of z statistics
s	vector of corresponding significands of the standard error
z0	significance threshold. Can be a single number like 1.96 or a vector of length z
h	half-width of considered window around z0

Value

A data frame with risk of missclassification information for each observations. We illustrate the columns for the misclassification risk: "s.misclass" is the threshold for the significand s above which we can rule out misclassification risk risk.misclass = s < s.misclass indicates whether the observation is at risk of misclassification risk.misclass.below = risk.misclass & z < z0 indicates whether the observation is at risk of misclassification and below the significance threshold the other columns should be self-explainable given this info.