rmcorr {rmcorr}

Calculate the repeated measures correlation coefficient.

Description

Calculate the repeated measures correlation coefficient.

Usage

rmcorr(
  participant,
  measure1,
  measure2,
  dataset,
  CI.level = 0.95,
  CIs = c("analytic", "bootstrap"),
  nreps = 100,
  bstrap.out = F
)

Arguments

participant

A variable giving the subject name/id for each observation.

measure1

A numeric variable giving the observations for one measure.

measure2

A numeric variable giving the observations for the second measure.

dataset

The data frame containing the variables.

CI.level

The confidence level of the interval

CIs

The method of calculating confidence intervals.

nreps

The number of resamples to take if bootstrapping.

bstrap.out

Determines if the output include the bootstrap resamples.

Value

A list with class "rmc" containing the following components.

r

the value of the repeated measures correlation coefficient.

df

the degrees of freedom

p

the p-value for the repeated measures correlation coefficient.

CI

the 95% confidence interval for the repeated measures correlation coefficient.

model

the multiple regression model used to calculate the correlation coefficient.

resamples

the bootstrap resampled correlation values.

References

Bakdash, J.Z., & Marusich, L.R. (2017). Repeated Measures Correlation. Frontiers in Psychology, 8, 456, doi:10.3389/fpsyg.2017.00456.

Bakdash, J. Z., & Marusich, L. R. (2019). Corrigendum: Repeated Measures Correlation. Frontiers in Psychology, 10, doi:10.3389/fpsyg.2019.01201.

Bland, J.M., & Altman, D.G. (1995a). Calculating correlation coefficients with repeated observations: Part 1 – correlation within subjects. BMJ, 310, 446, doi:10.1136/bmj.310.6977.446

Bland, J.M., & Altman, D.G. (1995b). Calculating correlation coefficients with repeated observations: Part 2 – correlation within subjects. BMJ, 310, 633, doi:10.1136/bmj.310.6980.633

See Also

plot.rmc, geom_rmc

Examples

## Bland Altman 1995 data
rmcorr(Subject, PaCO2, pH, bland1995)