Advanced Quantitative Research Methods for Urban Planners

Reid Ewing, Keunhyun Park, Reid Ewing, Keunhyun Park

• Publisher: Routledge
• Year: 2020
• Print ISBN: 9780367343279
• eBook ISBN: 9781000036442
• Topic: Architecture
• Subtopic: Méthodes et matériel d'architecture

Advanced Quantitative Research Methods for Urban Planners provides fundamental knowledge and hands-on techniques about research, such as research topics and key journals in the planning field, advice for technical writing, and advanced quantitative methodologies.

This book aims to provide the reader with a comprehensive and detailed understanding of advanced quantitative methods and to provide guidance on technical writing. Complex material is presented in the simplest and clearest way possible using real-world planning examples and making the theoretical content of each chapter as tangible as possible. Hands-on techniques for a variety of quantitative research studies are covered to provide graduate students, university faculty, and professional researchers with useful guidance and references.

A companion to Basic Quantitative Research Methods for Urban Planners, Advanced Quantitative Research Methods for Urban Planners is an ideal read for researchers who want to branch out methodologically and for practicing planners who need to conduct advanced analyses with planning data.

1
Introduction

Divya Chandrasekhar, Fatemeh Kiani, Sadegh Sabouri, Fariba Siddiq, and Keunhyun Park

The world is an increasingly complex place, and the tools we use to understand it are also growing in sophistication. There are many reasons for this. Quantitative researchers of today wish to understand the world more holistically—to move away from traditional methods that isolate phenomena in order to study them and to move toward ways of studying phenomena within their broader (but also deeper) context. Researchers of today also desire to push the field of quantitative analysis beyond its historical legacy of what? questions to questions of how? and why?

Researchers in the field of planning are not an exception. With the adoption of rigorous techniques, researchers are seeking to address the complex and multifaceted issues in urban planning. In this, they are aided by the changing nature of the data: More studies are employing mixed methods designs, producing more discrete and categorical data, and doing so in much larger quantities. The advent of big data provides tremendous explanatory power to quantitative research, but it also demands methodological innovations that embrace the complexity of data instead of rejecting it.

Changing times need novel ways of thinking, and the purpose of this book is to introduce urban planning researchers to some of these novel, sophisticated ways. This book has two main objectives: first, to provide the reader with a comprehensive and detailed understanding of innovative, advanced quantitative methods in urban planning, and second, to provide guidance on technical writing since much of scientific advancement is predicated upon effective communication of research findings. To the editors’ knowledge, there is no such book with detailed guidance on the use of advanced research methods and their applicability in urban planning research. The audience for this book is primarily doctoral students and early career researchers in urban planning, although those in allied fields such as geography, public administration, public health, and sociology may also find it useful.

The readers of the book are expected to have a basic knowledge of statistics and quantitative research. Descriptive statistics, t-test, ANOVA test, correlation, and chi-square have been referred to in different chapters of this book. Particularly, understanding regression analysis is critical because more advanced methods, such as multilevel modeling, Poisson regression, and structural equation modeling, are subject to the same caveats and limitations as linear regression analysis. Violating the assumptions of the model may lead to inefficient and/or biased parameter estimators. Other problems that can similarly affect nonlinear estimators include multicollinearity of independent variables, omitted variables, misspecification, dependence of cases or observations on one another, and small sample sizes.

Companion Book: Basic Quantitative Research Methods for Urban Planners

Readers interested in learning about introductory concepts in quantitative research are directed to the companion book in this series: Basic Quantitative Research Methods for Urban Planners. That book is aimed at master’s-level students in urban planning and allied fields who wish to enter professional practice. The book introduces the reader to key definitions and concepts in general social science research (Chapter 1), a guide to writing skills and techniques for urban planners (Chapter 2), types of empirical research design (Chapter 3), data types and sources in urban planning research (Chapter 4), and other important concepts in quantitative research including conceptual frameworks (Chapter 5), validity and reliability (Chapter 6), descriptive statistics (Chapter 7), inferential statistics (Chapter 8 to 13), and quasi-experimental design (Chapter 14). Notably, logistic regression analysis and quasi-experimental research techniques are included in Basic Quantitative Research Methods for Urban Planners instead of this one. The editors hope to encourage more planning professionals to use these relatively advanced techniques and, in their turn, push the field forward.

Structure of the Advanced Methods Book

This book is laid out in 11 chapters, each coauthored by a leading expert in advanced analytical methods and one or more doctoral students in urban planning—a nod to the importance of our student community in driving methodological innovations. Chapter 2 introduces the basics of technical writing and publication. It is often useful to start research with the end product in mind because it helps select the right frame and tool for the exercise—a bit like outlining a design before coloring in the details. And just like drawing, this is an iterative exercise, often requiring that the outline (i.e., the main argument) or the coloring (i.e., the data analysis) be adjusted to suit each other.

In Chapter 3, Terzano and others describe the journey between completing a manuscript and publishing it. The chapter covers considerations for choosing a journal (such as impact factor, ranking, and topical match) and the peer-review process, and it describes common article topics in planning-related journals. In the latter half of the chapter, the authors analyze the column “Research You Can Use” in Planning magazine as a basis for identifying currently common topics of interest in urban planning research, such as methodological issues, climate change and the natural environment, social justice, and sprawl, travel, and the built environment. The authors hope to help t...

Table of contents

• Cover
• Half Title
• Title
• Copyright
• Contents
• 1 Introduction
• 2 Technical Writing
• 3 Planning Journals and Topics
• 4 Poisson and Negative Binomial Regression Analysis
• 5 Principal Component and Factor Analysis
• 6 Cluster Analysis
• 7 Multilevel Modeling
• 8 Structural Equation Modeling
• 9 Spatial Econometrics
• 10 Meta-Analysis and Meta-Regression
• 11 Mixed-Methods Research
• List of Contributors
• Index