PBCAR/PThelper: Systematic Cleaning, Processing, and Summarizing of Behavioral Economic Purchase Task Data

A series of functions that introduce the steps needed to: i) Pre-process raw purchase task data; ii) Calculate empirical indicators from the data or derive values via equation; iii) Manage calculated indicators; and iv) Summarize purchase task indicators. Pre-processing includes detecting non-systematic data using a 4-criterion method, a modified version of the 3-criterion method set forth by Stein et al. (2015). These criteria are customizable for the user, and can accommodate purchase tasks that are partially-administered, such as those administered using an array method or until zero-consumption is reached. Empirically-derived purchase tasks indicators (Intensity, Breakpoint, Omax, Pmax) can be calculated from the data directly, as can equation-derived purchase tasks indicators (alpha, eta, Q0, unit elasticity, AUC) using the exponentiated demand equation (Koffarnus et al., 2015), a linear equation, or area-under-the-curve (Amlung et al., 2015).

install.packages("remotes")
remotes::install_github("PBCAR/PThelper")