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About 10,000 papers for “multiple regression model”

Multiple regression model.

Ahlam Badreldin El Shikieri (16378501) · Figshare · 2023

<p>The severity of food insecurity and its associated factors.</p> <p>(DOCX)</p>

Cited by 0Open access

Multiple regression model.

Walter Hugo Diaz Pinaya (2836580), Francisco Javier Lobon-Cervia (2836583), Pablo Pita (2836574) et al. · Figshare · 2016

<p>Best significant results for the CPUE of each taxnomic family, fishing ground and fishing environment from multiple regression. Significant values p < 0.05 and 2 degrees of freedom.</p>

Cited by 0Open access

Multiple regression model 1.

Mohammad Sabeeh Ul Haq (21402663), Dua Nilofar Jawed (21402666), Nehrish Patel (21402669) et al. · Figshare · 2025

<div> Objective This study aimed to investigate levels of anxiety/anxiety symptoms and coping methods employed among patients suffering from myocardial infarction admitted in a tertiary care setting in a developing country. It also aimed to study the relationship of anxiety levels and coping strategies with each other and also the influence of various socio-demographic factors on anxiety levels and coping strategies used by the patients. Methods A cross-sectional study was conducted at National Institute of Cardiovascular Disease (NICVD), Karachi, Pakistan involving 203 patients diagnosed with myocardial infarction. Sampling was conducted by non-probability convenience method. Patients were asked to fill a questionnaire comprising a socio-demographic form, HAM – A scale for anxiety symptoms and brief COPE scale for coping methods. Statistical analysis was performed using independent t-test, ANOVA, MANOVA, Pearson correlation and multiple regressions. Results Study comprised 203 patients (134 male, 69 female), 36.9% of the patients showed anywhere from moderate to severe levels of anxiety. Gender, history of myocardial infarction, family visits and hospital satisfaction were found to have statistical significance in influencing mean HAM – A scores among the population. Significant differences in problem focused coping was found among different gender and socio economic classes, while avoidance focused coping differences were found between patients receiving family visits and drug users as well as perceived hospital satisfaction. Hospital satisfaction also influenced emotional focused coping. Conclusion This research highlights the importance of providing integrated psychological support for patients with myocardial infarction, specifically on anxiety and coping methods. By examining these factors, we can better understand how they influence mental health outcomes. Addressing anxiety and enhancing effective coping strategies are crucial for improving overall recovery and quality of life for these patients. </div>

Cited by 0Open access

Multiple linear regression model.

Kristina Hörnberg (4715259), Björn Sundström (4715256), Lena Innala (4715262) et al. · Figshare · 2017

&lt;p&gt;Variables in early disease associated with aerobic capacity (ml/kg/min) at follow-up.&lt;/p&gt;

Cited by 0Open access

Multiple Regression Model Specification

Paul M. Kellstedt, Guy D. Whitten · Cambridge University Press eBooks · 2021

An R Companion for the Third Edition of The Fundamentals of Political Science Research offers students a chance to delve into the world of R using real political data sets and statistical analysis techniques directly from Paul M. Kellstedt and Guy D. Whitten's best-selling textbook. Built in parallel with the main text, this workbook teaches students to apply the techniques they learn in each chapter by reproducing the analyses and results from each lesson using R. Students will also learn to create all of the tables and figures found in the textbook, leading to an even greater mastery of the core material. This accessible, informative, and engaging companion walks through the use of R step-by-step, using command lines and screenshots to demonstrate proper use of the software. With the help of these guides, students will become comfortable creating, editing, and using data sets in R to produce original statistical analyses for evaluating causal claims. End-of-chapter exercises encourage this innovation by asking students to formulate and evaluate their own hypotheses.

Cited by 0

Multiple Model Regression Estimation

Vladimir Cherkassky, Yao Ma · IEEE Transactions on Neural Networks · 2005

This paper presents a new learning formulation for multiple model estimation (MME). Under this formulation, training data samples are generated by several (unknown) statistical models. Hence, most existing learning methods (for classification or regression) based on a single model formulation are no longer applicable. We describe a general framework for MME. Then we introduce a constructive support vector machine (SVM)-based methodology for multiple regression estimation. Several empirical comparisons using synthetic and real-life data sets are presented to illustrate the proposed approach for multiple model regression formulation.

Cited by 54

Multiple regression model 3.

Mohammad Sabeeh Ul Haq (21402663), Dua Nilofar Jawed (21402666), Nehrish Patel (21402669) et al. · Figshare · 2025

<div> Objective This study aimed to investigate levels of anxiety/anxiety symptoms and coping methods employed among patients suffering from myocardial infarction admitted in a tertiary care setting in a developing country. It also aimed to study the relationship of anxiety levels and coping strategies with each other and also the influence of various socio-demographic factors on anxiety levels and coping strategies used by the patients. Methods A cross-sectional study was conducted at National Institute of Cardiovascular Disease (NICVD), Karachi, Pakistan involving 203 patients diagnosed with myocardial infarction. Sampling was conducted by non-probability convenience method. Patients were asked to fill a questionnaire comprising a socio-demographic form, HAM – A scale for anxiety symptoms and brief COPE scale for coping methods. Statistical analysis was performed using independent t-test, ANOVA, MANOVA, Pearson correlation and multiple regressions. Results Study comprised 203 patients (134 male, 69 female), 36.9% of the patients showed anywhere from moderate to severe levels of anxiety. Gender, history of myocardial infarction, family visits and hospital satisfaction were found to have statistical significance in influencing mean HAM – A scores among the population. Significant differences in problem focused coping was found among different gender and socio economic classes, while avoidance focused coping differences were found between patients receiving family visits and drug users as well as perceived hospital satisfaction. Hospital satisfaction also influenced emotional focused coping. Conclusion This research highlights the importance of providing integrated psychological support for patients with myocardial infarction, specifically on anxiety and coping methods. By examining these factors, we can better understand how they influence mental health outcomes. Addressing anxiety and enhancing effective coping strategies are crucial for improving overall recovery and quality of life for these patients. </div>

Cited by 0Open access

Multiple regression model 2.

Mohammad Sabeeh Ul Haq (21402663), Dua Nilofar Jawed (21402666), Nehrish Patel (21402669) et al. · Figshare · 2025

<div> Objective This study aimed to investigate levels of anxiety/anxiety symptoms and coping methods employed among patients suffering from myocardial infarction admitted in a tertiary care setting in a developing country. It also aimed to study the relationship of anxiety levels and coping strategies with each other and also the influence of various socio-demographic factors on anxiety levels and coping strategies used by the patients. Methods A cross-sectional study was conducted at National Institute of Cardiovascular Disease (NICVD), Karachi, Pakistan involving 203 patients diagnosed with myocardial infarction. Sampling was conducted by non-probability convenience method. Patients were asked to fill a questionnaire comprising a socio-demographic form, HAM – A scale for anxiety symptoms and brief COPE scale for coping methods. Statistical analysis was performed using independent t-test, ANOVA, MANOVA, Pearson correlation and multiple regressions. Results Study comprised 203 patients (134 male, 69 female), 36.9% of the patients showed anywhere from moderate to severe levels of anxiety. Gender, history of myocardial infarction, family visits and hospital satisfaction were found to have statistical significance in influencing mean HAM – A scores among the population. Significant differences in problem focused coping was found among different gender and socio economic classes, while avoidance focused coping differences were found between patients receiving family visits and drug users as well as perceived hospital satisfaction. Hospital satisfaction also influenced emotional focused coping. Conclusion This research highlights the importance of providing integrated psychological support for patients with myocardial infarction, specifically on anxiety and coping methods. By examining these factors, we can better understand how they influence mental health outcomes. Addressing anxiety and enhancing effective coping strategies are crucial for improving overall recovery and quality of life for these patients. </div>

Cited by 0Open access

Multiple linear regression model.

Kristina Hörnberg (4715259), Björn Sundström (4715256), Lena Innala (4715262) et al. · Figshare · 2017

&lt;p&gt;Variables in early disease associated with aerobic capacity (ml/kg/min) at follow-up.&lt;/p&gt;

Cited by 0Open access

Multiple Regression Model Specification

Paul M. Kellstedt, Guy D. Whitten · Cambridge University Press eBooks · 2013

In this chapter we provide introductory discussions of and advice for commonly encountered research scenarios involving multiple regression models. Issues covered include dummy independent variables, interactive specifications, influential cases, and multicollinearity.

Cited by 1

The Multiple Regression Model

2016

This appendix expands the regression model from the single independent variable case to situations that require the inclusion of multiple independent variables, as is the norm for most practical applications.

Cited by 1Open access