Preface

It took 10 years to organize this e-book. I was introduced to general linear models as a teaching assistant in 2012 in the Measurement and Statistics (M & S) Program at Florida State University (FSU). At the time I was struck by the power of the analytic techniques – a suite of statistical knowledge and techniques for drawing analytical conclusions from a set of numeric values. At the same time, I was struck by the fundamental limitations (e.g., violations of regression assumptions; deficiency on validity evidence in measurement model, parameter choices; missingness including nonresponse bias, etc.) of the applicability of the techniques, especially when applied to the field of public management and policy. I left the program with the impression that statistics was attractive but ultimately not very useful for the researchers to explore and examine public sector organizations. I vowed to monitor progress in the field.

I returned to the program in 2015 and learned in-depth analytical techniques since that time. I earned my PhDs in the dual-degree programs of M & S and Public Administration (PA) and Policy. The past decade has been an exciting time for my academic journey as computer technology has developed rapidly, particularly in the area of psychometrics. These developments have coupled with the ever-increasing quality of quantitative research in the social sciences. My disciplines aim to be unified by both critical thinking and technical practice. To do so, with a focus on interdisciplinarity and collaboration, I have worked to bridge analytical techniques and the public management agendas. Contrary to my prediction that other disciplines could collaborate, in reality, the perspectives of applied statisticians, such as psychometricians, and econometricians, were far narrower than we thought, and communication between them did not seem easy. So, I thought it would be quicker for myself, with substantive knowledge in public policy and management, to reach policy problem solving scientifically by accomplishing the interdisciplinary integration of them in me.

With skepticism about the current research situation that research problems and research methodology are playing separately, it is necessary to consider how much we contribute to the discovery of scientific facts. I believe that PA scholars and students applying reflective thinking to public management should accept recent advances in econometrics and decision-making support systems (DSS), including tree-based methods, kernel-based methods, and artificial neural networks as everyone does. Why it is a problem that scholars get stuck in an ideology or theory, is because they try to apply the old theories that fill their heads to solve social challenges. You have to grab the most pressing points of the time and look into the problems, always have a humble perception that your tools can be wrong, and have an integrated attitude with a variety of approaches.

Analytic Techniques for Public Management and Policy was written with the hope where the techniques can be used effectively to be evidence-based research and that it might encourage public management and policy researchers to inform more effective governance. This e-book is based on ordinary least squares (OLS) regression and is informed by four resources: Dr. Russell G. Almond’s statistics classes, Dr. Salih Binici’s measurement classes, Dr. Tom Cook’s quasi-experimental design workshop, and Dr. Kyoung-jun Lee’s DSS class. I am very grateful to Dr. Almond at the FSU, Dr. Binici at the Florida State Department of Education, Dr. Cook at Northwestern University, and Dr. Lee at Kyung Hee University.