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R Package with auxiliary functions to facilitate data pre-processing and analysis of behavioral data

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behavdata

CC BY-NC-SA 4.0

DOI

Introduction

The behavdata package allows easy pre-processing and analysis of behavioral data. This package includes the following functions:

Scale Analysis Related

  • likert_transform: for fastly transforming text inputs like from Likert scale answers into numerical values
  • likert_switch: to invert numerical values Likert scales
  • AlphaCI_Bounds: to determine the confidence interval for Cronbach's Alpha values
  • combined_scaleanalysis: To quickly determine standard values for scale analyses
  • scales: An extension of the function combined_scaleanalysis
  • likert_means_4p: Average Likert score for 4-point Likert scales
  • likert_means_5p: Average Likert score for 5-point Likert scales
  • likert_means_7p: Average Likert score for 7-point Likert scales
  • in.numeric: for transforming data on any scale (i.e., non-numeric Likert scale) into numeric valuess

Qualitative Data Related

  • answer_rating: for facilitated and unbiased rating of student answers on qualitative or open-ended questions

Correlation Analyses

  • correlation_table: to calculate all pairwise correlations of a big data set and directly obtain a CSV table
  • single_correlation_table: to calculate pairwise correlations of a single vector with many others and directly obtain a CSV table

Effect Size Analyses

  • eta_to_d: to calculate Cohen's d values from eta-squared scores
  • r_to_d: to calculate Cohen's d values from correlation values
  • f_to_d: to calculate Cohen's d values from ANOVA F scores
  • gse: to determine the standard error of Hedge's g effect sizes
  • finding_d: to determine the lowest Cohen's d value with which two group means are statistically equivalent
  • finding_d_from_df: to determine the lowest Cohen's d value with which two group means are statistically equivalent from a data frame

Outlier Analysis

  • outliers: to determine statistical outliers
  • truefalsecounter: compare two vectors to make a vector with true/false values to indicate where the values in vector 1 are present in vector 2

Other Functions

  • se_propagation: to propagate standard errors
  • ci_to_sd: to find standard deviation values from confidence intervals
  • pathback: to go one folder up in the working directory
  • stat.info: to get descriptive test statistics of numerical data
  • stat.info_chr: to get descriptive test information of non-numerical data
  • count_if: to count how many times a certain number or element is present in the data
  • p.signs: to assign symbols to p-values

More functions will be added over time.

Installation

library(devtools)
devtools::install_github("samueltobler/behavdata", force = TRUE)
library(behavdata)

Citation

To cite the repository behavdata in publications, please use:

Tobler, S. (2022). behavdata: R Package for Behavioral Data Preprocessing and Analysis (Version 0.1.1) [Computer software]. https://github.com/samueltobler/behavdata


If you used the finding_d function, please cite additionally:

Tobler, S. (2022, October). Finding equivalence: a novel tool to investigate the effect size at which two groups are statistically equivalent. In 7th Annual Learning Sciences Graduate Student Conference (LSGSC 2022). https://doi.org/10.3929/ethz-b-000575508


References

Some of the functions require previously published R packages. These are the references of these packages (in alphabetical order).

  • Hmisc: Harrell Jr F (2022). Hmisc: Harrell Miscellaneous. R package version 4.7-0, https://CRAN.R-project.org/package=Hmisc.
  • psych: Revelle, W. (2022) psych: Procedures for Personality and Psychological Research, Northwestern University, Evanston, Illinois, USA. https://CRAN.R-project.org/package=psych
  • sjmisc: Lüdecke D (2018). “sjmisc: Data and Variable Transformation Functions.” Journal of Open Source Software, 3 (26), 754. doi:10.21105/joss.00754
  • TOSTER: Lakens, D. (2017). Equivalence tests: A practical primer for t-tests, correlations, and meta-analyses. Social Psychological and Personality Science, 8(4), 355-362. doi:10.1177/1948550617697177

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R Package with auxiliary functions to facilitate data pre-processing and analysis of behavioral data

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