Secretaría de Gobernación
CONACYT
INGER
Por favor, use este identificador para citar o enlazar este ítem: http://repositorio.inger.gob.mx/jspui/handle/20.500.12100/17413
Título : Random intercept and linear mixed models including heteroscedasticity in a logarithmic scale: Correction terms and prediction in the original scale
Autor: RICARDO RAMIREZ ALDANA
LIZBETH NARANJO ALBARRAN
Palabras clave : MEDICINA Y CIENCIAS DE LA SALUD;Linear mixed models;Modelos lineales Mixtos;Personas mayores;Elder People;Heteroscedasticity
Fecha de publicación: 2021
Editorial : Plos One
Descripción : 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
Otros identificadores : https://doi.org/10.1371/journal.pone.0249910
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249910
Aparece en las colecciones: 1. Artículos