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Introduction to Regression Modeling Introduction to Regression Modeling

John G. Orme and Terri Combs-Orme

in Multiple Regression with Discrete Dependent Variables

Published in print:
2009
Published Online:
May 2009
ISBN:
9780195329452
eISBN:
9780199864812
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780195329452.003.0001
Subject:
Social Work, Research and Evaluation

This chapter is a brief review of some major concepts of linear regression, presented in the context of simple examples using both dichotomous and continuous independent variables. The chapter ... More


Semiparametric Mixed Models for Longitudinal Data

Ludwig Fahrmeir and Thomas Kneib

in Bayesian Smoothing and Regression for Longitudinal, Spatial and Event History Data

Published in print:
2011
Published Online:
September 2011
ISBN:
9780199533022
eISBN:
9780191728501
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199533022.003.0004
Subject:
Mathematics, Probability / Statistics, Biostatistics

This chapter considers Bayesian inference in semiparametric mixed models (SPMMs) for longitudinal data. Section 4.1 assumes Gaussian smoothness priors, focusing on Bayesian P-splines in combination ... More


Multi‐Level Modelling and Contingent Valuation

Ian H. Langford and Ian J. Bateman

in Valuing Environmental Preferences: Theory and Practice of the Contingent Valuation Method in the US, EU , and developing Countries

Published in print:
2001
Published Online:
November 2003
ISBN:
9780199248919
eISBN:
9780191595950
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/0199248915.003.0012
Subject:
Economics and Finance, Development, Growth, and Environmental

This chapter explores, in an introductory manner, the potential advantages of using multi‐level modelling in a range of contingent valuation (CV) survey designs. Section 12.2 briefly reviews the ... More


Random effects models for sibling and twin-based studies in life course epidemiology

Samuli Ripatti

in Family matters: Designing, analysing and understanding family based studies in life course epidemiology

Published in print:
2009
Published Online:
September 2009
ISBN:
9780199231034
eISBN:
9780191723841
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199231034.003.0011
Subject:
Public Health and Epidemiology, Public Health, Epidemiology

This chapter introduces statistical methods for twin and sibling studies using random effects models. The classic twin study begins from assessing the variance of a trait (called a phenotype by ... More


Introduction: Scope of the Book and Applications

Ludwig Fahrmeir and Thomas Kneib

in Bayesian Smoothing and Regression for Longitudinal, Spatial and Event History Data

Published in print:
2011
Published Online:
September 2011
ISBN:
9780199533022
eISBN:
9780191728501
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199533022.003.0001
Subject:
Mathematics, Probability / Statistics, Biostatistics

This introductory chapter begins with a discussion of semiparametric regression covering generalized linear models, generalized additive models, semiparametric mixed models, and spatial regression ... More


Getting Started with Generalized Linear Models

Andrew P. Beckerman, Dylan Z. Childs, and Owen L. Petchey

in Getting Started with R: An Introduction for Biologists

Published in print:
2017
Published Online:
March 2017
ISBN:
9780198787839
eISBN:
9780191829659
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198787839.003.0007
Subject:
Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies

We introduce generalized linear models (GLMs), demonstrating by comparison with a linear model when, why, and how these models can be valuable and important to the biologist. The chapter focuses on a ... More


Likelihood-Based Approaches to Modeling the Neural Code

Jonathan Pillow

in Bayesian Brain: Probabilistic Approaches to Neural Coding

Published in print:
2006
Published Online:
August 2013
ISBN:
9780262042383
eISBN:
9780262294188
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262042383.003.0003
Subject:
Neuroscience, Disorders of the Nervous System

This chapter discusses likelihood-based approaches to building mathematical models of the neural code. It introduces probabilistic neural models such as the linear-non-linear-Poisson (LNP) model ... More


Linear and generalized linear mixed models

Benjamin M. Bolker

in Ecological Statistics: Contemporary theory and application

Published in print:
2015
Published Online:
April 2015
ISBN:
9780199672547
eISBN:
9780191796487
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199672547.003.0014
Subject:
Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies, Ecology

Generalized linear mixed models (GLMMs) are a powerful class of statistical models that combine the characteristics of generalized linear models and mixed models (models with both fixed and random ... More


Some Regression Models for AF Measures

Sabina Alkire, James Foster, Suman Seth, Maria Emma Santos, José Manuel Roche, and Paola Ballón

in Multidimensional Poverty Measurement and Analysis

Published in print:
2015
Published Online:
August 2015
ISBN:
9780199689491
eISBN:
9780191793745
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199689491.003.0010
Subject:
Economics and Finance, Development, Growth, and Environmental

The chapter provides the reader with a general modelling framework for analysing the determinants of poverty measures presented in Chapter 5 for both micro and macro levels of analyses. At the micro ... More


Introduction

Andy Hector

in The New Statistics with R: An Introduction for Biologists

Published in print:
2015
Published Online:
March 2015
ISBN:
9780198729051
eISBN:
9780191795855
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198729051.003.0001
Subject:
Biology, Biomathematics / Statistics and Data Analysis / Complexity Studies, Ecology

The chapter sets out the aims of the book, the approach, what is covered in the book and what is not. The book starts by introducing several different variations of the basic linear model analysis ... More


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