Longitudinal Regression Models for Population Dynamics

Description

This book is an invaluable resource for all researchers interested in understanding practical applications of longitudinal regression methods. This book aims to equip readers with practical applications of longitudinal regression using case studies derived from administrative datasets such as the Australian government’s Person Level Integrated Data Asset (PLIDA). In providing practical examples... Read more

This book is an invaluable resource for all researchers interested in understanding practical applications of longitudinal regression methods. This book aims to equip readers with practical applications of longitudinal regression using case studies derived from administrative datasets such as the Australian government’s Person Level Integrated Data Asset (PLIDA). In providing practical examples concerning longitudinal regressions, a variety of administrative data is used, including examples not only from PLIDA but also from other sources like the Institute for Employment Research, Germany. These practical examples based on these data sources are generalisable to other data sources that readers may come across and use in their analytical research.

The author emphasises the applications of longitudinal regression methods, using substantial empirical illustrations, designed to help users of social research and data analysis to better analyse and understand linked administrative datasets. This book discusses numerous SAS procedures, such as PROC GLM for estimating fixed‑effects linear models, PROC LOGISTIC for estimating fixed‑effects logistic regression models, PROC PHREG for estimating fixed‑effects Cox regression models, and PROC GENMOD for estimating fixed‑effects Poisson regression models. Readers learn about the critical need for the proper handling of longitudinal data, including issues related to data privacy, anonymisation, and ethical considerations. By providing real‑world case studies and practical examples, this book bridges the gap between theoretical knowledge and practical implementation, offering valuable guidance for researchers and practitioners.

The primary audience for this book comprises social researchers and academics who engage in advanced analytical research, utilising longitudinal datasets across a variety of domains, including income, employment, health, social security, and education. This book is also well suited for statisticians, demographers, public policy analysts, and graduate students who focus on longitudinal studies to understand trends and patterns in population dynamics.

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Author(s)

Biography

Taylan Akay, PhD, currently works at the Department of Defence as a data specialist. He also works at the University of New South Wales (UNSW) Canberra at the Australian Defence Force Academy (ADFA) as a postdoctoral senior research associate, advancing AI ethics for autonomous weapon systems. Dr Akay’s career spans rigorous analytic roles across the Department of Defence, Social Services, and Home Affairs, where he has crafted scalable machine learning models, driven cloud migration strategies, and implemented enterprise data governance frameworks. Based in Canberra, he earned a PhD in economics at the Royal Melbourne Institute of Technology (RMIT) University and a master’s in applied finance at Monash University.

Longitudinal Regression Models for Population Dynamics

Description

Table of Contents

Author(s)

Biography

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