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