| precisionMeasures {superb} | R Documentation |
Precision measures
Description
superb comes with a few built-in measures of
precisions. All SE.fct() functions produces an interval width;
all CI.fct() produces the lower and upper limits of an interval.
See (Harding et al. 2014; Harding et al. 2015) for more.
"superbPlot-compatible" precision measures must have these parameters:
Usage
SE.mean(x)
CI.mean(x, gamma)
SE.median(x)
CI.median(x, gamma)
SE.hmean(x)
CI.hmean(x, gamma)
SE.gmean(x)
CI.gmean(x, gamma)
SE.var(x)
CI.var(x, gamma)
SE.sd(x)
CI.sd(x, gamma)
SE.MAD(x)
CI.MAD(x, gamma)
SE.IQR(x)
CI.IQR(x, gamma)
SE.fisherskew(x)
CI.fisherskew(x, gamma)
SE.pearsonskew(x)
CI.pearsonskew(x, gamma)
SE.fisherkurtosis(x)
CI.fisherkurtosis(x, gamma)
Arguments
x |
a vector of numbers, the sample data (mandatory); |
gamma |
a confidence level for CI (default 0.95). |
Value
a measure of precision (SE) or an interval of precision (CI).
References
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.
Examples
# the confidence interval of the mean for default 95% and 90% confidence level
CI.mean( c(1,2,3) )
CI.mean( c(1,2,3), gamma = 0.90)
# Standard errors for standard deviation, for MAD and for fisher skew
SE.sd( c(1,2,3) )
SE.MAD( c(1,2,3) )
SE.fisherskew( c(1,2,3) )