Secretaría de Gobernación
CONACYT
INGER
Please use this identifier to cite or link to this item: http://repositorio.inger.gob.mx/jspui/handle/20.500.12100/17413
Title: Random intercept and linear mixed models including heteroscedasticity in a logarithmic scale: Correction terms and prediction in the original scale
metadata.dc.creator: RICARDO RAMIREZ ALDANA
LIZBETH NARANJO ALBARRAN
Keywords: MEDICINA Y CIENCIAS DE LA SALUD;Linear mixed models;Modelos lineales Mixtos;Personas mayores;Elder People;Heteroscedasticity
metadata.dc.date: 2021
Publisher: Plos One
Description: Random intercept models are linear mixed models (LMM) including error and intercept random effects. Sometimes heteroscedasticity is included and the response variable is transformed into a logarithmic scale, while inference is required in the original scale; thus, the response variable has a log-normal distribution. Hence, correction terms should be included to predict the response in the original scale. These terms multiply the exponentiated predicted response variable, which subestimates the real values. We derive the correction terms, simulations and real data about the income of elderly are presented to show the importance of using them to obtain more accurate predictions. Generalizations for any LMM are also presented.
URI: http://repositorio.inger.gob.mx/20.500.12100/17413
Other Identifiers: https://doi.org/10.1371/journal.pone.0249910
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249910
Appears in Collections:1. Artículos