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"Dynamical correlation: A new method for quantifying synchrony with multivariate intensive longitudinal data":

    Psychological Methods
    |May 30, 2018
    PubMed
    Summary

    An error in the original R script for dynamical correlation analysis has been corrected. An updated script is available, ensuring accurate significance testing for synchrony in intensive longitudinal data.

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    Area of Science:

    • Psychological Methods
    • Statistical Analysis
    • Data Science

    Background:

    • The original article introduced dynamical correlation, a novel method for quantifying synchrony in multivariate intensive longitudinal data.
    • Dynamical correlation offers advantages over existing methods like multilevel modeling, being a nonparametric approach suitable for irregularly spaced observations.

    Purpose of the Study:

    • To report and correct errors found in the R script provided in the original publication.
    • To provide an updated and validated R script for accurate dynamical correlation analysis and significance testing.

    Main Methods:

    • Identification and correction of errors in the R script's functions ('ind_DC', 'boot_test_DC').
    • Removal of specific arguments ('na', 'ms') and addition of data validation for missing values.

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  • Clarification of argument labels and provision of a downloadable, corrected R script.

    • Main Results:

    • The original R script contained errors potentially leading to incorrect significance testing for dynamical correlation.
    • An updated R script has been developed, addressing these errors and improving data handling for missing values.

    Conclusions:

    • The corrected R script ensures reliable estimation and significance testing of dynamical correlation.
    • Researchers can now utilize the updated script for accurate analysis of synchrony in intensive longitudinal data.