Studying Human Populations

This textbook is for graduate students and research workers in social statistics and related subject areas. It follows a novel curriculum developed around the basic statistical activities: sampling, measurement and inference.

This is a textbook for graduate students and research workers in social statistics and related subject areas. It follows a novel curriculum developed around the basic statistical activities of sampling, measurement and inference. Statistics is defined broadly as making decisions in the presence of uncertainty that arises as a consequence of limited resources available for collecting information. A connecting link of the presented methods is the perspective of missing information, catering for a diverse class of problems that include nonresponse, imperfect measurement and causal inference. The monograph aims to prepare the reader for the career of an independent social statistician and to serve as a reference for methods, ideas for and ways of studying human populations.

Text for competent practitioners of statistics, not future statisticians Suitable as reference Includes supplementary material: sn.pub/extras

Autorentext

Nick Longford received his doctorate in Statistics from Leeds University, England, in 1982. Since 2004 he has served as the Director of SNTL Statistics Research and Consulting in Barcelona, Spain. He has been a visitor at several academic institutions, most recently CEPS/INSTEAD in Esch, Luxembourg (2011, 2012 and 2013), Universidad de Valle, Colombia (2011 and 2013), la Sapienza, Rome, Italy (2009 and 2010) and Universitat Pompeu Fabra, Barcelona, Spain (intermittently since 2005). His previous monographs with Springer have dealt with methods for large-scale educational assessment (1995), missing data and small-area estimation (2005), and statistics curriculum for the social sciences (2008). His journal articles have been published in the Journals of the Royal Statistical Society, Statistics in Medicine, Computational Statistics and Data Analysis, Statistica Neerlandica, Survey Methodology, Journal of Educational and Behavioral Statistics, Journal of Applied Statistics and others.

Inhalt
ANOVA and Ordinary Regression.- Maximum Likelihood Estimation.- Sampling Methods.- The Bayesian Paradigm.- Incomplete Data.- Imperfect Measurement.- Experiments and Observational Studies.- Clinical Trials.- Random Coefficients.- Generalised Linear Models.- Longitudinal and Time-Series Analysis.- Meta-Analysis and Estimating Many Quantities.