Program Evaluation: Embedding Evaluation into Program Design and Development provides an in-depth examination of the foundations, methods, and relevant issues in the field of evaluation. With an emphasis on an embedded approach, where evaluation is an explicit part of a program that leads to the refinement of the program, students will learn how to conduct effective evaluations that foster continual improvement and enable data-based decision making. This text provides students with both the t...

Designed to reduces students' anxieties and minimize unnecessary formulas, this fourth edition provides a comprehensive introduction to basic statistical designs and analyses.

Whether students are doing interviews in their own research or just using other researchers' data, this book tells them everything they need to know about designing, planning, conducting and analyzing quality interviews.

This practical book uses a step-by-step analysis of realistic examples to help students understand the theory and code for implementing propensity score analysis with the R statistical language.

A step-by-step on five different qualitative approaches - thematic analysis, interpretative phenomenological analysis, grounded theory, narrative analysis and discourse analysis.

An R Companion to Applied Regression is a broad introduction to the R statistical computing environment in the context of applied regression analysis.

Drawing on the expertise of major names in the field, this text provides comprehensive coverage of the key methods for analyzing, interpreting, and writing up qualitative research in a single volume.

A sophisticated introduction to the diversity and interconnectivity of digital space, technology, objects, people and data. It sets out the theory and methods needed to understand digital life and then links them to real world data showcasing their strengths and challenges.Â

An invaluable step-by-step, pedagogically engaging guide to data management in R for social science researchers. This book shows students how to recode and document data, as well as how to combine data from different sources, or import from statistical packages other than R.