Binary Recursive Partitioning 1 Running head: BINARY RECURSIVE PARTITIONING Binary recursive partitioning: Background, methods, and application to psychology

Binary recursive partitioning (BRP) is a computationally-intensive statistical method that can be used in situations where linear models are often used. Instead of imposing many assumptions to arrive at a tractable statistical model, BRP simply seeks to accurately predict a response variable based on values of predictor variables. The method outputs a decision tree depicting the predictor variables that were related to the response variable, along with the nature of the variables ’ relationships. No significance tests are involved, and the tree’s “goodness ” is judged based on its predictive accuracy. In this paper, we describe BRP methods in a detailed manner and illustrate their use in psychological research. We also provide R code for carrying out the methods. Binary Recursive Partitioning 3 Binary recursive partitioning: Background, methods, and application to psychology Binary recursive partitioning (BRP), also referred to as Classification and Regression Trees (CART)1, is a computationally-intensive statistical method that is ofte