---
title: Predictor Variables with Random Forests
url: https://www.ml-quant.com/papers/repec/sae-jedbes-v-49-y-2024-i-4-p-595-629/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:sae:jedbes:v:49:y:2024:i:4:p:595-629
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fjournals.sagepub.com%2Fdoi%2F10.3102%2F10769986231193327%3Bh%3Drepec%3Asae%3Ajedbes%3Av%3A49%3Ay%3A2024%3Ai%3A4%3Ap%3A595-629
featured: 2024-08-07
citations: unknown
topic: ML & AI Methods
---


# Predictor Variables with Random Forests

The study compares variable selection with random forests, a machine learning method, with linear models in behavioral sciences, providing practical advice.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fjournals.sagepub.com%2Fdoi%2F10.3102%2F10769986231193327%3Bh%3Drepec%3Asae%3Ajedbes%3Av%3A49%3Ay%3A2024%3Ai%3A4%3Ap%3A595-629
- Identifier: RePEc:sae:jedbes:v:49:y:2024:i:4:p:595-629
- Released: 2024-08-07
- First featured: Quant Letter No. 60 (2024-08-07): https://www.ml-quant.com/issues/2024-08-07/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: ML & AI Methods

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