### **Project Overview** ### **This page contains PLS analysis code and data associated with:** Meidenbauer, K. L., Niu, T., Choe, K. W., Stier, A. J., & Berman, M. G. (2022). Mouse movements reflect personality traits and task attentiveness in online experiments. *Journal of Personality.* https://doi.org/10.1111/jopy.12736 *KLM & TN contributed equally to this work **Anonymized data & code for calculating mouse movement variables, initial data pre-processing and quality checks, and univariate statistical analyses can be found on Tianyue (Selina) Niu's Github page:** **https://github.com/tianyueniu/mouse_movement_personality** ### **Project Components** ### #### **Data** #### ##### **Inputs for PLS** #### The data that are read into the PLS analysis scripts are two CSV files which do not include participant identifiers but the order of participants is maintained by row number, so they can be read in separately without issue - *personalityMouseExtractedFeatures.csv* contains the mouse movements and task attentiveness data (AUC) - *personalityMouseSelfReport.csv* contains the Big Five personality scores, Age, and Gender (coded as 0 = Male, 1 = Female) ##### **Aggregate CSV file** ##### - *personality_mouse_final_table.csv* is the aggregate CSV file for any of the univariate statistical analyses. It can also be found on Selina's github page above. ##### **PLS output for e2 effect size calc** ##### - *Mouse_Vmat_Big5_Umat_Mousetrack_Person_PLS.mat* is one of the saved outputs from the PLS analysis scripts. It is the current file corresponding to the effect size calculator script below, but any of the saved .mat files from the PLS scripts will work in the effect size calculation with some modifications. #### **Analysis Scripts** #### ##### **Code for PLS Analysis** ##### All PLS analyses were conducted in Matlab 2018b. To run these analyses, the base PLS analysis code must be downloaded from https://www.rotman-baycrest.on.ca/ - *Run_BehavPLS_mousetracking_personality.m* is the main PLS analysis file - *Read_clicks_columns.m* is a helper function that reads in the mousetracking variables - *Read_personal_demo.m* is a helper function that reads in the personality and demographic variables ##### **Code for e2 (e-squared) effect size** ##### Effect size analysis was conducted in Matlab 2018b. - *mousetracking_effect_size.m* is the base code to calculate the pseudo R-squared (e2) effect size for PLS analysis. ##### **R code for plot generation** ##### - *make_plots_mousetracking_personality.R* makes the age x personality scatterplots (in Figure 2) and the correlogram (Figure 3)