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