Artwork courtesy of Chelsea Parlett Pelleriti

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SimplyAgree is an R package, and jamovi module, created to make agreement and reliability analyses easier for the average researcher. The functions within this package include simple tests of agreement (agree_test), agreement analysis for nested (agree_nest) and replicate data (agree_reps), and provide robust analyses of reliability (reli_stats). In addition, this package contains a set of functions to help when planning studies looking to assess measurement agreement (blandPowerCurve).

Installing SimplyAgree

You can install the most up-to-date version of SimplyAgree from GitHub with:

devtools::install_github("arcaldwell49/SimplyAgree")

References

The functions in this package are largely based on the following works:

Lin L (1989). A concordance correlation coefficient to evaluate reproducibility. Biometrics 45: 255 - 268. https://doi.org/10.2307/2532051

Shieh, G. (2019). Assessing agreement between two methods of quantitative measurements: Exact test procedure and sample size calculation. Statistics in Biopharmaceutical Research, 1-8. https://doi.org/10.1080/19466315.2019.1677495

Parker, R. A., et al (2016). Application of mixed effects limits of agreement in the presence of multiple sources of variability: exemplar from the comparison of several devices to measure respiratory rate in COPD patients. Plos one, 11(12), e0168321. https://doi.org/10.1371/journal.pone.0168321

Zou, G. Y. (2013). Confidence interval estimation for the Bland–Altman limits of agreement with multiple observations per individual. Statistical methods in medical research, 22(6), 630-642. https://doi.org/10.1177/0962280211402548

Weir, J. P. (2005). Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. The Journal of Strength & Conditioning Research, 19(1), 231-240.

Lu, Meng-Jie, et al (2016). “Sample Size for Assessing Agreement between Two Methods of Measurement by Bland−Altman Method” The International Journal of Biostatistics, 12(2), https://doi.org/10.1515/ijb-2015-0039

King, TS and Chinchilli, VM. (2001). A generalized concordance correlation coefficient for continuous and categorical data. Statistics in Medicine, 20, 2131:2147.

King, TS, Chinchilli, VM, and Carrasco, JL. (2007). A repeated measures concordance correlation coefficient. Statistics in Medicine, 26, 3095:3113.

Carrasco, JL, et al. (2013). Estimation of the concordance correlation coefficient for repeated measures using SAS and R. Computer Methods and Programs in Biomedicine, 109, 293-304.