CV: Coefficient of Variation (CV), or typical percentage error...

In psr: Functions for Analyzing Performance Science Data

Description

Computes the CV for each vector of measurements that is passed to the function, for the subject and trial vectors

Usage

CV(subject, trial, ...)

Arguments

subject	The vector of athletes who recorded the results for each metric (can be a numeric or factor variable)
trial	The vector that represents which trial each measurement came from
...	Numeric vectors that represent the metrics for which the CV should be computed. These vectors hold the scores that each athlete recorded for each respective metric (at least one metric must be passed to the function).

Value

A data frame, with the name of each metric situated above its calculated CV

References

Hopkins, W. G. (2000). Measures of Reliability in Sports Medicine and Science. Sports Medicine, 30(5), 375-381.

Examples

subject <- c(1, 1, 1, 2, 2, 2, 3, 3, 3)
trial <- c(1, 2, 3, 1, 2, 3, 1, 2, 3)
metric_1 <- c(250, 258, 252, 279, 270, 277, 218, 213, 218)
metric_2 <- c(10, 7, 10, 14, 18, 17, 11, 7, 8)
metric_3 <- c(1214, 1276, 1289, 1037, 1010, 1069, 1481, 1465, 1443)
CV(subject, trial, metric_1, metric_2, metric_3)

psr documentation built on Aug. 13, 2021, 5:08 p.m.