superb adds a few summary statistics that can
be used to characterize a dataset. All comes with SE.fct() and CI.fct().
See (Harding et al. 2014; Harding et al. 2015)
for more.
superbPlot-compatible summary statistics functions must have one parameter:
hmean(x)
gmean(x)
MAD(x)
fisherskew(x)
pearsonskew(x)
fisherkurtosis(x)a vector of numbers, the sample data (mandatory);
a summary statistic describing the sample.
Harding B, Tremblay C, Cousineau D (2014).
“Standard errors: A review and evaluation of standard error estimators using Monte Carlo simulations.”
The Quantitative Methods for Psychology, 10(2), 107--123.
Harding B, Tremblay C, Cousineau D (2015).
“The standard error of the Pearson skew.”
The Quantitative Methods for Psychology, 11(1), 32--36.
# the confidence interval of the mean for default 95% and 90% confidence level
gmean( c(1,2,3) ) # the geometric mean; also available in psych::geometric.mean
#> [1] 1.817121
hmean( c(1,2,3) ) # the harmonic mean; also available in psych::harmonic.mean
#> [1] 1.636364
MAD( c(1,2,3) ) # the median absolute deviation to the median (not the same as mad)
#> [1] 1
fisherskew( c(1,2,3) ) # the Fisher skew corrected for sample size
#> [1] 0
fisherkurtosis( c(1,2,3) ) # the Fisher kurtosis corrected for sample size
#> [1] NaN
pearsonskew( c(1,2,3) ) # the Pearson skew
#> [1] 0