Repeated Measures Correlation

Compute the repeated measures correlation, a statistical technique for determining the overall within-individual relationship among paired measures assessed on two or more occasions, first introduced by Bland and Altman (1995). Includes functions for diagnostics, p-value, effect size with confidence interval including optional bootstrapping, as well as graphing. Also includes several example datasets. For more details, see Bakdash and Marusich (2017) .


Repeated measures correlation (rmcorr) is a statistical technique for determining the common within-individual association for paired measures assessed on two or more occasions for multiple individuals.


# install.packages("devtools")


rmcorr(Subject, PacO2, pH, bland1995)
#> Warning in rmcorr(Subject, PacO2, pH, bland1995): 'Subject' coerced into a
#> factor
#> Repeated measures correlation
#> r
#> -0.5067697
#> degrees of freedom
#> 38
#> p-value
#> 0.0008471081
#> 95% confidence interval
#> -0.7112297 -0.223255


rmcorr 0.3.0

  • column names can be entered as strings and dynamically
  • dataset parameter is no longer required in the plot.rmc function
  • Added a file to track changes to the package.

Reference manual

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0.4.4 by Laura R. Marusich, 3 months ago

Browse source code at

Authors: Jonathan Z. Bakdash , Laura R. Marusich

Documentation:   PDF Manual  

GPL-2 license

Imports stats, grDevices, graphics, psych, RColorBrewer

Suggests knitr, rmarkdown, plotrix, ggplot2, lme4, merTools, pwr, AICcmodavg, pals

Suggested by correlation.

See at CRAN