TL;DR: The three-volume Encyclopedia of Research Design elucidates how one makes decisions about research design, interprets data and draws valid inferences, undertakes research projects in an ethical manner, and evaluates experimental design strategies and results.
Abstract: Research design, with its statistical underpinnings, can be especially daunting for students and novice researchers. At its heart, research design might be described simply as a formalized approach toward problem solving, thinking, and acquiring knowledge, the success of which depends upon clearly defined objectives and appropriate choice of statistical design and analysis to meet those objectives. Our three-volume Encyclopedia of Research Design elucidates how one makes decisions about research design, interprets data and draws valid inferences, undertakes research projects in an ethical manner, and evaluates experimental design strategies and results. From A-to-Z, this work covers the spectrum of research design strategies and topics including, among other things: fundamental research design principles, ethics in the research process, quantitative versus qualitative and mixed-method designs, completely randomized designs, multiple comparison tests, diagnosing agreement between data and models, fundamental assumptions in analysis of variance, factorial treatment designs, complete and incomplete block designs, Latin square and related designs, hierarchical designs, response surface designs, split-plot designs, repeated measures designs, crossover designs, analysis of covariance, statistical software packages, and much more.
TL;DR: A case study methodology that combines a real-time longitudinal three-year study with nine retrospective case studies about the same phenomenon and enhances three kinds of validity: construct, internal and external is described.
Abstract: This paper describes a case study methodology that combines a real-time longitudinal three-year study with nine retrospective case studies about the same phenomenon. These two kinds of case studies offer opportunities for complementary and synergistic data gathering and analysis. That is, specific strengths in each method compensate for some particular weakness in the other. For instance, the retrospective studies offer the opportunity to identify patterns indicative of dynamic processes and the longitudinal study provides a close-up view of those patterns as they evolve over time. The combination of the two types of case studies also enhances three kinds of validity: construct, internal and external. The author also discusses problems with and shortcomings of this dual methodology and suggests the circumstances for which the methodology is especially appropriate.
TL;DR: In this paper, the authors provide a knowledge of how to design a high quality mixed methods research study, and explain the seven major design dimensions: purpose, theoretical drive, timing (simultaneity and dependency), point of integration, typological versus interactive design approaches, planned versus emergent design, and design complexity.
Abstract: This article provides researchers with knowledge of how to design a high quality mixed methods research study. To design a mixed study, researchers must understand and carefully consider each of the dimensions of mixed methods design, and always keep an eye on the issue of validity. We explain the seven major design dimensions: purpose, theoretical drive, timing (simultaneity and dependency), point of integration, typological versus interactive design approaches, planned versus emergent design, and design complexity. There also are multiple secondary dimensions that need to be considered during the design process. We explain ten secondary dimensions of design to be considered for each research study. We also provide two case studies showing how the mixed designs were constructed.
TL;DR: The development and application of a methodology that uses protocol studies of designers engaged in design to investigate the process of designing is described and results are shown that illustrate the utility of this approach in gaining some insight into how designers design.
TL;DR: This article argues that ideal longitudinal research is characterized by the seamless integration of three elements: a well-articulated theoretical model of change observed using a temporal design that affords a clear and detailed view of the process, with the resulting data analyzed by means of a statistical model that is an operationalization of the theoretical model.
Abstract: This article argues that ideal longitudinal research is characterized by the seamless integration of three elements: (a) a well-articulated theoretical model of change observed using (b) a temporal design that affords a clear and detailed view of the process, with the resulting data analyzed by means of (c) a statistical model that is an operationalization of the theoretical model. Two general varieties of theoretical models are considered: models in which the time-related change of primary interest is continuous, and those in which it is characterized by movement between discrete states. In addition, two general types of temporal designs are considered: the longitudinal panel design and the intensive longitudinal design. For each general category of theoretical models, some of the analytic possibilities available for longitudinal panel designs and for intensive longitudinal designs are discussed. The article concludes with brief discussions of two issues particularly relevant to longitudinal research--missing data and measurement--and a few words about exploratory research.