DBERlibR is an R package developed by Helikar Lab at the University of Nebraska-Lincoln for automated assessment data analyses. Some of the most frequently used statistical techniques are developed into functions to clean the data, merge/bind multiple data sets (as necessary), check assumption(s) for a specific statistical technique (as necessary), run the main assessment data analysis, and print the outputs in R console. The outputs contain a sample interpretation of the results for the convenience of users. Users need to prepare the data file as instructed.

This function automatically reads and cleans the data (e.g., converting missing values to “0”), calculates difficulty and discriminant scores, and prints the results in the R console and Plots panel.

This function automatically reads and cleans the data sets (e.g., converting missing values to "0), merges pre-post data sets, runs the (parametric) paired samples T-test and (nonparametric) Wilcoxon signed-rank test, and then prints outputs in the R console and Plots panel to help users examine the difference between pre-post scores.

This function automatically reads and cleans the data sets (e.g., converting missing values to "0), binds treatment-control group data sets, runs the independent samples t-test (parametric) and Mann–Whitney U test (nonparametric), and then prints the results in the R console and Plots panel to help users examine the difference between the groups.

This function can be used to analyze the difference between two groups (e.g., intervention vs. control group) with a covariate (e.g., pre-test scores) controlled. The function automatically merges pre-post data sets, binds treatment-control data sets, runs scripts to check assumptions of one-way ANCOVA, runs the main one-way ANCOVA and post hoc analyses, and then displays all outputs in the R console and Plots panel for users all at once.

This function can be used when you collect data from the same students repeatedly at three different time points (e.g., pre-test, post-test, and post2-test) and you want to examine the significance of the changes over time. The function automatically merges pre, post, and post2 data sets, runs the one-way repeated measures ANOVA with assumptions check, and then displays the outputs in the R console and Plots panel for users all at once.

This function automatically combines demographic variables to a data set, runs the analysis of variance (ANOVA) with assumptions check to examine demographic sub-group differences, and then displays the outputs in the R console and Plots panel for users all at once.