# SEM: Standard Error of Measurement (SEM) for a set of athlete... In psr: Functions for Analyzing Performance Science Data

## Description

Computes the SEM for each metric that is passed to the function as a vector of measurements, for the subject and trial vectors and the ICC's of the metrics

## Usage

 `1` ```SEM(subject, trial, ..., ICC) ```

## 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 SEM 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). `ICC` A vector of the ICC's for each of the metrics included in the "..." argument. This vector must contain the same number of elements as the number of metrics that have been passed to the function in the "..." argument, and the reliability values must appear in the same order as the metrics appear in the "..." argument.

## Value

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

## References

Atkinson, G., & Nevill, A. M. (1998). Statistical Methods For Assessing Measurement Error (Reliability) in Variables Relevant to Sports Medicine. Sports Medicine, 26(4), 217-238.

## Examples

 ```1 2 3 4 5 6``` ```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) SEM(subject, trial, metric_1, metric_2, metric_3, ICC = c(0.92, 0.98, 0.95)) ```

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