Regression Models for Right Censoring

2018 ◽  
pp. 14-16
Author(s):  
MISSING-VALUE MISSING-VALUE
Keyword(s):  
Regression Models ◽  
Right Censoring

scholarly journals Mastery and Longevity in Spousal Caregivers of Persons with Dementia

2019 ◽  
Vol 75 (7) ◽  
pp. 1558-1562
Author(s):  
Jyoti Savla ◽  
Zhe Wang ◽  
Jiafeng Zhu ◽  
Nancy Brossoie ◽  
Karen A Roberto ◽  
...  
Keyword(s):  
Regression Models ◽  
Cox Regression ◽  
Right Censoring ◽  
Spousal Caregivers ◽  
Coping Resource ◽  
Time To Death ◽  
Personal Mastery ◽  
Risk Of Death ◽  
Reduced Risk

Abstract Objective Researchers have consistently shown that providing care in a gradually deteriorating situation, such as dementia, can be stressful and detrimental to the caregiver’s (CG) health. Although stressor appraisal is important in understanding variability in CG outcomes, the role of personal mastery, a coping resource, in shaping CG’s health outcomes has not been considered. The primary goal of this paper was to determine whether personal mastery is associated with a survival advantage for spousal CGs of persons with dementia. Methods This study assessed the association of CG burden and personal mastery with longevity over a 10-year period in 71 spousal CGs of persons initially diagnosed with mild cognitive impairment. Results Over the 10 years, 16 of 71 CGs (23%) died. Cox regression models with right censoring of CGs’ time to death showed that after adjusting for the health of family CG, spousal CGs who reported high levels of burden had an 83% reduced risk of death when they also reported high personal mastery (hazard ratio [HR] = 0.17, 95% confidence interval [CI] 0.04, 0.65). Conclusions Findings have implications for support programs that help build personal mastery.

scholarly journals Empirical Likelihood for Generalized Functional-Coefficient Regression Models with Multiple Smoothing Variables under Right Censoring Data

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Hong-Xia Xu ◽  
Han-Sheng Zhong ◽  
Guo-Liang Fan
Keyword(s):  
Empirical Likelihood ◽  
Unknown Parameter ◽  
Regression Models ◽  
Confidence Region ◽  
Right Censoring ◽  
Likelihood Method ◽  
True Parameter ◽  
Empirical Likelihood Method ◽  
Nonparametric Approach ◽  
Functional Coefficient

Empirical likelihood as a nonparametric approach has been demonstrated to have many desirable merits for constructing a confidence region. The purpose of this article is to apply the empirical likelihood method to study the generalized functional-coefficient regression models with multiple smoothing variables when the response is subject to random right censoring. The coefficient functions with multiple smoothing variables can accommodate various nonlinear interaction effects between covariates. The empirical log-likelihood ratio of an unknown parameter is constructed and shown to have a standard chi-squared limiting distribution at the true parameter. Based on this, the confidence region of the unknown parameter can be constructed. Simulation studies are carried out to indicate that the empirical likelihood method performs better than a normal approximation-based approach for constructing the confidence region.

A Multivariate Approach to Lexical Diversity in Constrained Language

2020 ◽  
Vol 21 (2) ◽  
pp. 169-194
Author(s):  
Marta Kajzer-Wietrzny ◽  
Ilmari Ivaska
Keyword(s):  
Second Language Acquisition ◽  
Regression Models ◽  
Translation Studies ◽  
Methodological Framework ◽  
Multivariate Approach ◽  
Mediated Communication ◽  
Vocabulary Size ◽  
Lexical Diversity ◽  
Linear Mixed Effects ◽  
Word Repetition

Empirical Translation Studies have recently extended the scope of research to other forms of constrained and mediated communication, including bilingual communication, editing, and intralingual translation. Despite the diversity of factors accounted for so far, this new strand of research is yet to take the leap into intermodal comparisons. In this paper we look at Lexical Diversity (LD), which under different guises, has been studied both within Translation Studies (TS) and Second Language Acquisition (SLA). LD refers to the rate of word repetition, and vocabulary size and depth, and previous research indicates that translated and non-native language tends to be less lexically diverse. There is, however, no study that would investigate both varieties within a unified methodological framework. The study reported here looks at LD in spoken and written modes of constrained and non-constrained language. In a two-step analysis involving Exploratory Factor Analysis and linear mixed-effects regression models we find interpretations to be least lexically diverse and written non-constrained texts to be most diverse. Speeches delivered impromptu are less diverse than those read out loud and the non-constrained texts are more sensitive to such delivery-related differences than the constrained ones.

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