Results 241 to 250 of about 208,783 (277)

Generalized linear mixed model for monitoring autocorrelated logistic regression profiles

The International Journal of Advanced Manufacturing Technology, 2012
Profile monitoring is used to monitor the regression relationship between a response variable and one or more explanatory variables over time. Many researches have been done in this area, but in most of them, the distribution of the response variable is assumed to be normal. However, this assumption is violated in many real case problems.
Mehdi Koosha, Amirhossein Amiri
openaire   +1 more source

Generalized Linear Models I: Logistic Regression

2001
All of the models discussed so far assume that the dependent variable is continuous and normally distributed. In this chapter, we introduce generalized linear models, which include the regression and ANOVA models of previous chapters, but can also be used for modeling non-normally distributed response variables, in particular categorical variables.
Brian Everitt, Sophia Rabe-Hesketh
openaire   +1 more source

Effects of the housing price to income ratio on tenure choice in Taiwan: forecasting performance of the hierarchical generalized linear model and traditional binary logistic regression model

Journal of Housing and the Built Environment, 2017
This study examined factors that influence the tenure choices of households in different counties and cities of Taiwan. Data collected in the Housing Status Survey by the Construction and Planning Agency of the Ministry of the Interior were analyzed using hierarchical generalized linear modeling (HGLM).
Chun-Chang Lee, Chih-Min Liang, Jian-Zheng Chen, Cheng-Huang Tung   +3 more
openaire   +1 more source

More on the generalized linear model: logistic and loglinear models

2019
This chapter discusses sub-frameworks of the generalized linear model (GLZM) which can be used for nominal-level data with two categories (binary logistic model) and scale data in the form of counts (loglinear model). It examines how they can be used to assess the relative effects of multiple explanatory (independent) variables on a single response ...
openaire   +1 more source

[Logistic regression vs other generalized linear models to estimate prevalence rate ratios].

Revue d'epidemiologie et de sante publique, 2000
In cross-sectional studies, to quantify the association between a risk factor and a disease (possibly adjusted for confounders), in the framework of the multiplicative model, the more obvious effect measure is a prevalence rate ratio with an associated confidence interval.
P, Traissac, Y, Martin-Prével, F, Delpeuch, B, Maire   +3 more
openaire   +1 more source

PREDICTING MATHEMATICAL ANXIETY: A COMPARATIVE ANALYSIS OF RANDOM FOREST, LOGISTIC REGRESSION, AND HIERARCHICAL GENERALIZED LINEAR MODELS USING PYTHON

МАТЕМАТИКА, ФИЗИКА ЖӘНЕ ИНФОРМАТИКАНЫ ОҚЫТУДЫҢ ӨЗЕКТІ МӘСЕЛЕЛЕРІ
Math anxiety is a significant concern for many educators and policymakers due to its negative impact on students' math performance and career prospects. Various empirical studies have been conducted to examine the factors predicting math anxiety, typically based on a limited set of predefined variables, such as math performance and students' self ...
Mustafa ÖZKAN, G.K. Yeshmurat, L.S. Kainbayeva   +2 more
openaire   +1 more source

Phrase break prediction using logistic generalized linear model

Interspeech 2006, 2006
Lifu Yi, Jian Li, Xiaoyan Lou, Jie Hao
openaire   +1 more source

Multicriteria emergency decision for responding to man overboard casualties: A proposed procedure developed using Binary Logistics Regression and General Linear Models

Ocean Engineering, 2022
Orhan Gonel, Ismail Cicek
openaire   +1 more source

The Generalized Linear Model: Logistic and Poisson Regression

2018
Scott A. Pardo, Michael A. Pardo
openaire   +1 more source

Interpreting Interaction Effects in Generalized Linear Models of Nonlinear Probabilities and Counts

Multivariate Behavioral Research, 2022
Connor J Mccabe, Max A Halvorson, Kevin M King   +2 more
exaly