Letter to the Editor

TL;DR

This paper critically evaluates a recently proposed Monte Carlo EM algorithm for linear quantile mixed models, demonstrating that its claimed advantages over previous methods are unfounded and highlighting inaccuracies in the original work.

Contribution

The paper provides a critical analysis showing that the new Monte Carlo EM approach does not outperform existing methods and identifies errors in the original publication.

Findings

The Monte Carlo EM method does not improve over previous approaches.

Several inaccuracies in Galarza, Lachos, and Bandyopadhyay (2017) are identified.

The claims of methodological superiority are refuted.

Abstract

Galarza, Lachos and Bandyopadhyay (2017) have recently proposed a method of estimating linear quantile mixed models (Geraci and Bottai, 2014) based on a Monte Carlo EM algorithm. They assert that their procedure represents an improvement over the numerical quadrature and non-smooth optimization approach implemented by Geraci (2014). The objective of this note is to demonstrate that this claim is incorrect. We also point out several inaccuracies and shortcomings in their paper which affect other results and conclusions that can be drawn.