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Chapter 5: Research Design - Coggle Diagram
Chapter 5: Research Design
Methods
Positive Methods: laboratory experiments and survey research are aimed at theory (or hypotheses). Employ a deductive approach to research, starting with theory and testing theoretical postulates using empirical data.
Interpretive Methods: employ an indictive approach that starts with data and tries to derive a theory about the phenomenon of interest from the observed data.
Mixed-mode Designs: combine qualitative and quantitative data to generate unique insight a complex social phenomenon.
Key Attributes of a Research Design
Internal Validity: examines whether the observed change in a dependent variable is indeed causes by a corresponding change in hypothesized independent variable, and not by variables extraneous to the research context.
External Validity: refers to whether the observed associations can be generalized from the sample to the population, or to other people, organizations, contexts, or time.
Cone Validity: research designs that have reasonable degrees of both internal and external validities.
Construct Validity: examines how well a given measurement scale is measuring the theoretical construct that it is expected to measure.
Statistical Conclusion Validity: examines the extent to which conclusions derived using a statistical procedure is valid
Improving Internal and External Validity
Manipulation: researcher manipulates the independent variables in one or more levels, and compares the effects of the treatments against a control group where subject do not receive the treatment.
Elimination: relies on eliminating extraneous variable by holding them constant across treatments, such as by restricting the study to a single gender or a single socioeconomic status.
Inclusion: the role of extraneous variables is considered by including them in the research design and separately estimating their effects on the dependent variable.
Randomization: aimed at canceling out the effects of extraneous variables through a process of random sampling, if it can be assured that these effects are of a random nature.
Random selection: a sample is selected randomly from a population.
Random assignment: subjects selected in a non-random manner are randomly assigned to treatment groups.
Popular Research Designs
Experimental Studies: those intended to test cause-effect relationships in a tightly controlled setting by separating the cause from the effect in time, administering the cause to one group subjects but not to another group, and observing how the mean effects vary between subjects in these two groups.
True Experimental Design: subjects must be randomly assigned between each group.
Quasi-Experimental: when a random assignment is not followed.
Field Surveys: non-experimental designs that do not control for or manipulate independent variables or treatments, but measure these variables and test their effects using statistical methods.
Cross-Sectional Field Surveys: independent and dependent variables are measured at the same point in time.
Longitudinal Field Surveys: dependent variables are measured at a later point in time than the independent variables.
Secondary Data Analysis: an analysis of data that has previously been collected and tabulated by other sources
Popular Research Designs (continued)
Case Research: an in-depth investigation of a problem in one or more real-life settings over and extended period of time.
Multiple Case Design: replicating and comparing analysis in other case sites.
Focus Group Research: research that involves bringing in a small group of subjects at one location, and having them discuss a phenomenon of interest for a period of 1.5 to 2 hours.
Action Research: assumes that a complex social phenomenon are best understood by introducing interventions or "actions" into those phenomena and observing the effects of those actions.
Ethnography: an interpretive research design inspired by anthropology that emphasizes that research phenomenon must be studied within the context of its culture.