Bayesian penalized cumulative logit model for high‐dimensional data with an ordinal response

2020 ◽  
Author(s):  
Yiran Zhang ◽  
Kellie J. Archer
Keyword(s):  
Logit Model ◽  
High Dimensional Data ◽  
High Dimensional ◽  
Ordinal Response ◽  
Cumulative Logit Model ◽  
Cumulative Logit

Bayesian Approaches to Assessing the Parallel Lines Assumption in Cumulative Ordered Logit Models

2019 ◽  
pp. 004912411988246
Author(s):  
Jun Xu ◽  
Shawn G. Bauldry ◽  
Andrew S. Fullerton
Keyword(s):  
Health Research ◽  
Logit Model ◽  
Logit Models ◽  
Ordered Logit ◽  
Bayesian Approaches ◽  
Parallel Lines ◽  
Cumulative Logit Model ◽  
Cumulative Logit ◽  
Modeling Techniques ◽  
Null Values

We first review existing literature on cumulative logit models along with various ways to test the parallel lines assumption. Building on the traditional frequentist framework, we introduce a method of Bayesian assessment of null values to provide an alternative way to examine the parallel lines assumption using highest density intervals and regions of practical equivalence. Second, we propose a new hyperparameter cumulative logit model that can improve upon existing ones in addressing several challenges where traditional modeling techniques fail. We use two empirical examples from health research to showcase the Bayesian approaches.

scholarly journals Factors Affecting Levels of Antiretroviral Drug Adherence among Adult Patient Living with HIV in Public Health Facilities of Arba Minch Town, Southern Ethiopia: Using Cumulative Logit Model

2019 ◽  
pp. 1-9
Author(s):  
Sultan Hussen Hebo ◽  
Kabtamu Tolosie Gergiso ◽  
Markos Abiso Erango
Keyword(s):  
Antiretroviral Therapy ◽  
Marital Status ◽  
Logit Model ◽  
People Living With Hiv ◽  
Therapy Adherence ◽  
Cumulative Logit Model ◽  
Antiretroviral Therapy Adherence ◽  
Cumulative Logit ◽  
Study Participants ◽  
Living With Hiv

Background: Adherence to antiretroviral therapy is essential to reduce the multiplication of the virus and improve disease outcomes. The studies have reported a range of factors influencing antiretroviral therapy adherence at various levels. Almost all studies were modeling the factors based on binary categorization of the adherence. Objective: This study intended to determine the adherence level and its associated factors to antiretroviral therapy among adult people living with human immunodeficiency virus. Methods: This study was a cross-sectional study that employed among 391 adult patients that were selected by simple random sampling. The cumulative Logit model was used to examine the associations between the outcome of antiretroviral therapy adherence and independent variables. Results: The study participants with good level of antiretroviral therapy adherence (67.77%) were approximately four times higher than study participants with fair (17.39%) and good (14.83%) adherence levels. As the duration on ART changed from ≤12 months to >12 months, the odds of high adherence/less adherence increased with approximately 61% (p = 0.0347) across the full scale of adherence levels. The estimated odds of patients with a CD4 ≥ 200cells/mm3 was 1.65 (p = 0.0279) times toward poor level of antiretroviral therapy adherence than the estimated odds of patients with CD4 < 200cells/mm3. Study participants who have single marital status tending to have more poor level of adherence to antiretroviral therapy than patients with married marital status (p = 0.0003). Conclusion: Levels of adherence to the antiretroviral therapy is significantly determined by the duration on antiretroviral therapy, the number of CD4 counts, the types of initial antiretroviral therapy regimens and the marital status of adult people living with HIV/AIDS.

scholarly journals An extended cumulative logit model for detecting a shift in frequencies of sky-cloudiness conditions

2012 ◽  
Vol 117 (D16) ◽  
pp. n/a-n/a
Author(s):  
QiQi Lu ◽  
Xiaolan L. Wang
Keyword(s):  
Logit Model ◽  
Cumulative Logit Model ◽  
Cumulative Logit

scholarly journals Analysis of multivariate longitudinal substance use outcomes using multivariate mixed cumulative logit model

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaolei Lin ◽  
Robin Mermelstein ◽  
Donald Hedeker
Keyword(s):  
Substance Use ◽  
Logit Model ◽  
Time Trend ◽  
Logistic Regression Model ◽  
Proportional Odds ◽  
Covariate Effects ◽  
Cumulative Logit Model ◽  
Cumulative Logit ◽  
Proportional Odds Assumption ◽  
Males And Females

Abstract Background Longitudinal assessments of usage are often conducted for multiple substances (e.g., cigarettes, alcohol and marijuana) and research interests are often focused on the inter-substance association. We propose a multivariate longitudinal modeling approach for jointly analyzing the ordinal multivariate substance use data. Methods We describe how the binary random slope logistic regression model can be extended to the multi-category ordinal outcomes. We also describe how the proportional odds assumption can be relaxed by allowing differential covariate effects on different cumulative logits for multiple outcomes. Data are analyzed from a P01 study that evaluates the usage levels of cigarettes, alcohol and marijuana repeatedly across 8 measurement waves during 7 consecutive years. Results 1263 subjects participated in the study with informed consent, among whom 56.6% are females. Males and females show significant differences in terms of the time trend for substance use. Specifically, males showed steeper trends on cigarette and marijuana use over time compared to females, while less so for alcohol. For all three substances, age effects appear to be different for different cumulative logits, indicating the violation of proportional odds assumption. Conclusions The multivariate mixed cumulative logit model offers the most flexibility and allows one to examine the inter-substance association when proportional odds assumption is violated.

ESTIMATING THE INTENSITY OF INFECTION WITH SCHISTOSOMA JAPONICUM IN VILLAGERS OF LEYTE, PHILIPPINES. PART I: A BAYESIAN CUMULATIVE LOGIT MODEL. THE SCHISTOSOMIASIS TRANSMISSION & ECOLOGY PROJECT (STEP)

2005 ◽  
Vol 72 (6) ◽  
pp. 745-753 ◽  
Author(s):  
HÉLÈNE CARABIN ◽  
STEPHEN T. McGARVEY ◽  
LAWRENCE JOSEPH ◽  
CLARE M. MARSHALL ◽  
REMIGIO OLVEDA ◽  
...  
Keyword(s):  
Schistosoma Japonicum ◽  
Logit Model ◽  
Intensity Of Infection ◽  
Cumulative Logit Model ◽  
Cumulative Logit ◽  
Transmission Ecology

Strong Consistency of Maximum Likelihood Estimators in Sequential-Cumulative Logit Model

2015 ◽  
Vol 742 ◽  
pp. 445-448
Author(s):  
Chang Ming Yin ◽  
Xiao Jie Li ◽  
Dan Fu
Keyword(s):  
Maximum Likelihood ◽  
Logit Model ◽  
Strong Consistency ◽  
Maximum Likelihood Estimators ◽  
Maximum Likelihood Estimates ◽  
Parameter Vector ◽  
Mild Conditions ◽  
Cumulative Logit Model ◽  
Cumulative Logit ◽  
Strongly Consistent

In this article, for the sequential-cumulative logit model, we show that maximum likelihood estimates of regression parameter vector is asymptotically existence and strongly consistent under mild conditions

scholarly journals Suicidality Among Young Adolescents in Secondary Schools in Hong Kong

2020 ◽  
Author(s):  
Teris Cheung ◽  
Daniel Y. T. Fong ◽  
Susan Fan ◽  
Tommy K.H. Fong ◽  
Paul Yip
Keyword(s):  
Mental Health ◽  
Hong Kong ◽  
Secondary School ◽  
Logit Model ◽  
Secondary School Students ◽  
Young Adolescents ◽  
School Students ◽  
Cumulative Logit Model ◽  
Cumulative Logit ◽  
Suicidal Attempts

Abstract Background:Despite concerted effort in suicide research and prevention across countries, youth suicide remains a significant public health concern in Hong Kong and nationwide. This study examined the prevalence and correlates of suicidality among secondary school students in Hong Kong. Methods:Data were derived from the 2016 Youth Sexuality Survey initiated by the Family Planning Association of Hong Kong using a stratified random sample of 3,672 secondary school students aged 12 to 18 years in Hong Kong. Suicidality was measured in four progressive levels (suicidal ideation, suicidal plan, suicidal attempts and suicidal attempts requiring medical attention). Multivariable cumulative logit model analysis was used to identify significant risk factors of suicidality.Results:Female students reported more suicidality than their male counterparts (28.0% versus 17.0%, respectively). Multivariable cumulative logit model analysis showed that female gender, age, unhappy school life, disharmony with classmates, unhappy family life, living with mother, acceptance of mothers’ discipline, not sleeping for more than 9 hours on weekdays, alcohol consumption, non-suicidal self-injury, and dissatisfaction with life were significantly associated with suicidality. Limitations:Due to cross-sectional design, causality between suicidality, individual psychosocial and psychological characteristics cannot be established.Conclusions:Suicidal behaviour among Chinese young adolescents remains prevalent in Hong Kong. Family disintegration, school-related problems, and life satisfaction are significant predictors of suicidal behaviour in this study. There is a pressing need to restore optimal mental health among youth adolescents via interdisciplinary collaboration among schools, healthcare providers, stakeholders and mental health experts. The involvement of stakeholders in the community in suicide research and prevention is pivotal in mental health promotion for young adolescents.

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