Yin, R.K. (2003) Case study research: Design and methods (3rd edition). London: Sage.
Yin’s book is an outstanding guide for designing and analyzing case studies. He thoroughly addresses the steps in planning a study and then making meaning from the data. He quickly addresses the purpose of the case study, on the first page. “Case studies are the preferred strategy when how or why questions are being posed, when the investigator has little control over events, and when the focus is on a contemporary phenomenon within some real-life context.”
Yin makes an incredibly important point in a discussion about defining research questions. He said that a good study will have both substance questions that ask what the study is about, and form questions that answer who, where, when, why, and how. This is an essential part of any research project, and explaining it this way gives some perspective for where case study fits into the general field of methodologies.
In chapter 2, Yin defines research designs as “the logic that links the data to be collected (and the conclusions to be drawn) to the initial questions of the study.” This definition gets right at the heart of the purpose of a research design. Ask a question, determine the form of answers you want (who, when, where, why, how), and logically link them together. Using this method will give the researcher a preferred methodology for answering research questions consistently.
Yin identifies four conditions for case study design quality: construct validity, internal validity, external validity, and reliability. The research question will determine the appropriate unit of analysis, and the findings of the case study will generalize through theory building.
When planning a case study, Yin recommends using a pilot test to train the researcher in how to read the data. He argues that the pilot will allow the researcher to read the language of the case data and be able to spot the information. In a case study, and in most qualitative inquiry, the researcher must record and interpret simultaneously, so as to capture the changing pace of the scene. Practicing this in the scene of inquiry will help the researcher train their mind to the details of the data.
In his discussion of data collection, Yin argues that researchers should use multiple sources of evidence in their analysis to guarantee their findings are valid. Yin’s argument is well-developed; in his document section, for example, he says using multiple sources can correct misspelled names, clarify confusing subjects, and provide information counter to what has previously been collected, which allows the researcher to find the commonality among the sources to find the truth. However, Yin argues that while each piece of data may be true to itself, it might not be true in fact. Therefore, comparing levels of data is essential to determine accuracy.
In his explanation of data analysis, Yin included many models for how to analyze data based on the questions the researcher is trying to answer. This section is well-developed, introducing five ways to code and analyze the data. Yin’s depth is useful as a guide to analyzing data and is the strength of this section. He concludes with a chapter devoted to reporting case study information, and gives models for writing the report, again based on the research question. For visual research, this plan allows the researcher to begin with an idea or a question, and follow up with the appropriate methods for the visual data that is available.
The greatest asset to this book is its explication of the importance of the research question process. It makes a strong argument that the research question drives every subsequent decision in any study. Some data analysis techniques are best served for certain types of research questions, and some writing styles give the best clarity to certain research questions. Yin’s book is a practical guide to a research question based case study approach to research.