Software for Data Analysis

An introductory book provides theoretical concepts on time series analysis with plenty of intuitive insight of how exactly these models work. It covers a comprehensive and systematic account of financial econometric models: classic one-factor linear models (AR, MA, ARMA, Unit-root, ARCH, VAR, etc), and also multi-factor models and non-linear models. New edition adds chapters for PCA and MCMC too.

A comprehensive source on mixed data analysis, Analysis of Mixed Data: Methods & Applications summarizes the fundamental developments in the field. Case studies are used extensively throughout the book to illustrate interesting applications from economics, medicine and health, marketing, and genetics

The first part of this book is devoted to methods seeking relevant dimensions of data. The second part is devoted to clustering methods which constitute another method, often complementary to the methods described in the first part, to synthesize and to analyze the data.

The book carefully designs its approach, starting from single-level then to multi-level models, also provides the methodologies with broad practical examples (using R) and graphical displays. It gives useful guidance for social scientist and other applied statisticians into linear regression, logistic regression, GLM, and hierarchical models.

Dyadic data is a commonly found data structure in social psychology and social relations research. The authors describe and demonstrate several statistical methods, including multilevel and structural equation modeling approaches.

Bruce Thompson shows readers how to use the latest techniques for interpreting research outcomes as well as how to make statistical decisions that result in better research.
Thompson integrates a broad array of methods involving only a single dependent variable, ranging from classical and robust location descriptive statistics, through effect sizes, and on through ANOVA, multiple regression, loglinear analysis and logistic regression. Special features include SPSS and Excel demonstrations that offer opportunities, in the book’s datasets and on Thompson’s website.

This book present graphical methods for analysing data. Some methods are new and some are old, some require a computer and others only paper and pencil; but they are all powerful data analysis tools.

One of the best understandable econometrics books. Excellent discussions on classical linear regression model, and also explanations on other quatitative methods: survival models, Bayesian approach, panel data, neural networks, time series, etc.

Spatial data are an important source of scientific information. The book is designed to be a desk reference for all researchers just getting into the field of spatial data analysis as well as for seasoned spatial analysts.

The book provides clear identification of key issues in research design (i.e. measurement, sampling and causation) as well as major data collection techniques. Excellent balance between qualitative and quantitative methods. Integration of research ethics with the pertinent methodological topics.

This easy-to-use resource provides a clear explanation of mixed modeling techniques and theories and demonstrates the use of five popular statistical software procedures (SAS, SPSS, Stata, R/S-plus, and HLM) for fitting linear mixed models (LMMs) using real-world data.
The authors fit LMMs based on both general and hierarchical model specifications, develop the model-building process step-by-step, and demonstrate the estimation, testing, and interpretation of fixed-effect parameters and covariance parameters associated with random effects.

Focusing on an analysis of models and data that arise from repeated observations of a cross-section of individuals, households or firms, this book also covers important applications within business, economics, education, political science and other social science disciplines. The author introduces the foundations of longitudinal and panel data analysis at a level suitable for quantitatively oriented graduate social science students as well as individual researchers. He emphasizes mathematical and statistical fundamentals but also demonstrates substantive applications from across the social sciences. These applications are enhanced by real-world data sets and software programs in SAS and Stata.

A straightforward, comprehensive, and approachable guide to research as practiced by social scientists, the Fourteenth Edition of this "gold-standard" book gives readers the tools they need to apply research concepts practically, as both a researcher and a consumer. The author emphasizes the process by showing readers how to design and construct projects, introducing the various observation modes in use today, and answering critical questions about research methods-such as how to conduct online surveys and analyze both qualitative and quantitative data.