Challenging current modes of thinking, and covering areas not usually found in qualitative research texts such as social reality/ontology and quantum reality/mechanics, this book helps readers to choose and defend their research methods and to take their work beyond standard perspectives

With a particular focus on the complexities of cross-national, comparative survey research, explored by a team of international experts at local and national levels, this exciting new handbook provides readers with a cutting-edge resource.

John MacInnes takes the fear out of statistics for students, and helps to raise the standards of their quantitative methods skills, by clearly and accessibly introducing all that's needed to know about using secondary data and working with IBM SPSS Statistics.

Covering all aspects of the proposal process, from the most basic questions about form and style to the task of seeking funding, this Sixth Edition has been completely updated and revised to offer clear advice backed up with excellent examples.

A guide to the terms and phrases that partially shape the origins, purpose, logic, meaning and methods of the practices known as qualitative inquiry, this Fourth Edition has 20 additional terms as well as a Readers' Guide.

This book is ideal for looking at research undertaken with limited funds, using a small sample of convenience, in a health care setting with the primary objective of improving client care and obtaining better client outcomes.

Provides a practical, up-to-date treatment of evaluability assessment (EA) focused on application, and capturing the multidisciplinary appeal of EA with case studies from different disciplines.

Covers the important new developments in meta-analysis methods over the last 14 years

Placing into perspective the meaning of evidence for evaluation professionals and applied researchers, the contributors to this book - a veritable 'who's who' in evaluation - provide observations about the diversity and changing nature of credible evidence.

Provides a unified framework for both single-level and multilevel modeling of ordinal categorical data