While heated arguments between practitioners of qualitative and quantitative research have begun to test the very integrity of the social sciences, this monograph outlines a unified approach to valid descriptive and causal inference in qualitative research, where numerical measurement is either impossible or undesirable. The book demonstrates that the same logic of inference underlies both good quantitative and qualitative research designs. Providing precepts intended to stimulate and discipline thought, the authors explore issues related to framing research questions, measuring the accuracy of data and the uncertainty of empirical inferences, discovering causal effects and generally improving qualitative research. Among the specific topics addressed are interpretation and inference, comparative case studies, the construction of causal theories, dependent and explanatory variables, the limits of random selection, selection bias, and errors in measurement. Mathematical notation is occasionally used to clarify concepts, but no prior knowledge of mathematics or statistics is assumed.
The unified logic of inference that this book explicates should be useful to qualitative researchers i