Results 11 to 20 of about 134,556 (286)

Parameter Estimation and Hypothesis Testing of The Bivariate Polynomial Ordinal Logistic Regression Model

Mathematics, 2023
Logistic regression is one of statistical methods that used to analyze the correlation between categorical response variables and predictor variables which are categorical or continuous.
Marisa Rifada, Vita Ratnasari, Purhadi Purhadi   +2 more
doaj   +3 more sources

Adjcatlogit, Ccrlogit, and Ucrlogit: Fitting Ordinal Logistic Regression Models [PDF]

The Stata Journal: Promoting communications on statistics and Stata, 2014
In this article, I present three commands that perform adjacent-category logistic regression (adjcatlogit), constrained continuation-ratio logistic regression (ccrlogit), and unconstrained continuation-ratio logistic regression (ucrlogit) for ordered response data.
Morten Wang Fagerland
openaire   +3 more sources

The Comparison between Ordinal Logistic Regression and Random Forest Ordinal in Identifying the Factors Causing Diabetes Mellitus

Jambura Journal of Mathematics, 2023
Diabetes is one of the high-risk diseases. The most prominent symptom of this disease is high blood sugar levels. People with diabetes in Indonesia can reach 30 million people.
Assyifa Lala Pratiwi Hamid, Anwar Fitrianto, Indahwati Indahwati, Erfiani Erfiani, Khusnia Nurul Khikmah   +4 more
doaj   +1 more source

KLASIFIKASI TINGKAT KESEJAHTERAAN KELUARGA DI KECAMATAN SIDEMEN MENGGUNAKAN BOOTSTRAP AGGREGATING (BAGGING) REGRESI LOGISTIK ORDINAL

E-Jurnal Matematika, 2023
This research was conducted to determine the variables that have a significant impact on the stages of a well-off family in Sidemen Sub-district based on indicators obtained from the BKKBN and to classify the stages of a well-off family.
I GUSTI NGURAH SENTANA PUTRA, MADE SUSILAWATI, I PUTU WINADA GAUTAMA   +2 more
doaj   +1 more source

Prediction of the Fundus Tessellation Severity With Machine Learning Methods

Frontiers in Medicine, 2022
PurposeTo predict the fundus tessellation (FT) severity with machine learning methods.MethodsA population-based cross-sectional study with 3,468 individuals (mean age of 64.6 ± 9.8 years) based on Beijing Eye Study 2011.
Lei Shao, Xiaomei Zhang, Teng Hu, Yang Chen, Chuan Zhang, Li Dong, Saiguang Ling, Zhou Dong, Wen Da Zhou, Rui Heng Zhang, Lei Qin, Wen Bin Wei   +11 more
doaj   +1 more source

Predictive Factors for Pelvic Organ Prolapse (POP) in Iranian Women’s: An Ordinal Logistic Approch [PDF]

Journal of Clinical and Diagnostic Research, 2014
Introduction: To investigate the predictors factors of Pelvic Organ Prolapse (POP) in Iranian women by using ordinal logistic regression. Materials and Methods: The role of risk factors of POP was evaluated among 365 patients attending in two public ...
Ashraf Direkvand-Moghadam, Zeinab Ghazanfari, Kourosh Sayehmiri   +2 more
doaj   +1 more source

Ordinal logistic regression model on the level of job relevance of graduates

Desimal, 2023
The ordinal logistic regression model is one of the statistical models used to classify ordinal data. The purpose of this study is to identify the relevance of FKIP Muhammadiyah Pringsewu University Lampung graduates.
Rahma Faelasofi Sunanto, Khoirin Nisa
doaj   +1 more source

DEMOCRATIC THINKING AND CIVIC EDUCATION IN GREECE: AN ORDINAL LOGISTIC REGRESSION MODEL

İmgelem, 2022
This paper presents a research that was carried out in autumn of 2021in Thessaloniki, Greece. Main purpose was to find out the link between democratic behavior of Greek young adults and the civic education that is obtained in public secondary education ...
Anthony Papaoikonomou
doaj   +1 more source

Statistical Analysis of Ordinal Response Variable: A Comparative Study [PDF]

المجلة العراقية للعلوم الاحصائية, 2022
Response variables in biological phenomena vary between three types: numerical response variables, ordinal categorical response variables, and nominal categorical response variables. In statistical studies, handling ordinal variables varies in accordance
Liqaa Alhamdany, Zaid Tariq Salah
doaj   +1 more source

Using rank data to estimate health state utility models [PDF]

, 2006
In this paper we report the estimation of conditional logistic regression models for the Health Utilities Index Mark 2 and the SF-6D, using ordinal preference data.
Aki Tsuchiya, Anthony O’Hagan, Brazier, Brazier, Broome, Cairns, Christopher McCabe, Currim, Dolan, Dyer, Hausman, Jennifer Roberts, John Brazier, Katherine Stevens, Kind, Koop, Ljung, Lloyd, McFadden, Peter Gilks, Saigal, Thurstone, Torrance, Torrance, Torrance   +24 more
core   +1 more source