TripleR: an R package for social relations analyses based on round-robin designs

Area of Science:

• Social psychology
• Quantitative psychology
• Network analysis

Background:

• Social relations analyses (SRA) are crucial for understanding interpersonal dynamics.
• Existing software for SRA often lacks advanced features or is not accessible within the R environment.
• Round-robin designs are a common methodology for collecting social interaction data.

Purpose of the Study:

• To introduce TripleR, a novel R package designed for social relations analyses.
• To extend existing software capabilities by incorporating unimplemented methods for significance testing and missing value imputation.
• To provide an accessible tool for researchers conducting SRA with round-robin data.

Main Methods:

• Development of the TripleR package in R.
• Implementation of social relations models for round-robin data.
• Integration of significance testing methods for single groups (Lashley & Bond, 1997).
• Inclusion of procedures for handling missing data within the analysis framework.

Main Results:

• TripleR successfully calculates social relations analyses based on round-robin designs.
• The package incorporates advanced significance testing and missing value handling capabilities.
• Demonstrated usability through didactic examples, requiring minimal R knowledge.

Conclusions:

• TripleR enhances the analytical toolkit for social relations research within the R environment.
• The package facilitates more robust and comprehensive analyses of interpersonal dynamics.
• TripleR is a valuable resource for researchers utilizing round-robin designs in social science.