Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
A quantile regression estimator for interval-censored data
View through CrossRef
Abstract
We describe an estimating equation that can be used to fit quantile regression models to interval-censored data. The proposed estimator presents important advantages over the existing methods, and can be applied when the data are a mixture of interval-censored, left-censored, and right-censored observations. We describe estimation and inference, report simulation results, and apply the proposed method to analyze the Signal Tandmobiel® data. The necessary R code has been incorporated in the existing R package
c
t
q
r
$\mathtt{c}\mathtt{t}\mathtt{q}\mathtt{r}$
.
Title: A quantile regression estimator for interval-censored data
Description:
Abstract
We describe an estimating equation that can be used to fit quantile regression models to interval-censored data.
The proposed estimator presents important advantages over the existing methods, and can be applied when the data are a mixture of interval-censored, left-censored, and right-censored observations.
We describe estimation and inference, report simulation results, and apply the proposed method to analyze the Signal Tandmobiel® data.
The necessary R code has been incorporated in the existing R package
c
t
q
r
$\mathtt{c}\mathtt{t}\mathtt{q}\mathtt{r}$
.
Related Results
Generalized Estimator of Population Variance utilizing Auxiliary Information in Simple Random Sampling Scheme
Generalized Estimator of Population Variance utilizing Auxiliary Information in Simple Random Sampling Scheme
In this study, using the Simple Random Sampling without Replacement (SRSWOR) method, we propose a generalized estimator of population variance of the primary variable. Up to the fi...
Regression analysis of interval-censored failure time data with non proportional hazards models
Regression analysis of interval-censored failure time data with non proportional hazards models
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Interval-censored failure time data arises when the failure time of interest is known only to lie within an i...
Regression models with an interval-censored covariate
Regression models with an interval-censored covariate
El análisis de supervivencia trata de la evaluación estadística de variables que miden el tiempo transcurrido hasta un evento de interés. Una particularidad que ha de considerar el...
Survival analysis issues with interval-censored data
Survival analysis issues with interval-censored data
L'anàlisi de la supervivència s'utilitza en diversos àmbits per tal d'analitzar dades que mesuren el temps transcorregut entre dos successos. També s'anomena anàlisi de la història...
M-quantile estimation and discriminant analysis for heteroscedastic processes
M-quantile estimation and discriminant analysis for heteroscedastic processes
Estimation du M-quantile et analyse discriminante pour les processus hétéroscédastiques
En s'appuyant sur des techniques dans les domaines temporel et fréquentiel, ...
On the Efficiency of the newly Proposed Convex Olanrewaju-Olanrewaju Lo-oλγ(|θ|) Penalized Regression-Type Estimator via GLMs Technique.
On the Efficiency of the newly Proposed Convex Olanrewaju-Olanrewaju Lo-oλγ(|θ|) Penalized Regression-Type Estimator via GLMs Technique.
In this article, we proposed a novel convex penalized regression-type estimator, termed Olanrewaju-Olanrewaju penalized regression-type estimator, denoted by Lo-oλγ(|θ|) for ultra...
Modified Quantile Regression for Modeling the Low Birth Weight
Modified Quantile Regression for Modeling the Low Birth Weight
This study aims to identify the best model of low birth weight by applying and comparing several methods based on the quantile regression method's modification. The birth weight da...
Modified Kibria-Lukman (MKL) estimator for the Poisson Regression Model: application and simulation
Modified Kibria-Lukman (MKL) estimator for the Poisson Regression Model: application and simulation
Background:
Multicollinearity greatly affects the Maximum Likelihood Estimator (MLE) efficiency in both the linear regression model and the generalized linear m...