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Research Design ("blueprint") - a comprehensive plan for data…
Research Design ("blueprint") - a comprehensive plan for data collection in an empirical research project that: 1). answers specific research questions; 2). tests specific hypotheses; 3). must specify at least 3 processes
Data Collection Methods
Positivist Methods - aimed at theory/hypotheses testing; employ deductive approach to research, starting with a theory and testing theoretical postulates using empirical data (i.e., laboratory experiments & survey research)
Interpretive Methods - employ an inductive approach that starts with data and tries to derive a theory about the phenomenon of interest from the observed data (i.e., using quantitative techniques such as regression or qualitative techniques such as coding).
Processes: 1). data collection process ("research design"); 2). instrument development process; 3). sampling process
4 Key Design Attributes
Internal Validity ("causality") - examines whether the observed change in a dependent variable is indeed caused by a corresponding change in hypothesized independent variable, and not by variables extraneous to the research content.
3 Conditions of Causality: 1). covariation of cause & effect (i.e., if cause happens, then effect also happens and if cause does not happen, effect does not happen); 2). temporal precedence: cause must precede effect in time; 3). no plausible alternative explanation (or spurious correlation).
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External Validity ("generalizability") - refers to whether the observed associations can be generalized from the sample to the population (population validity), or to other people, organizations, contexts, or time (ecological validity).
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.
Popular Research Designs
Experimental Studies - those that are intended to test cause-effect relationships (hypotheses) in a tightly controlled setting by separating the cause from the effect in time, administering the cause to one group of subjects, but not to another group, and observing how the mean effects vary between subjects in these two groups. * True experimental designs require subjects to be randomly assigned between each group and if random assignment is not followed, then the design becomes quasi-experimental.
Field Surveys - non-experimental designs that do not control for 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 (e.g., using a single questionnaire.
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.
Case Research - an in-depth investigation of a problem in one or more real-life settings (case sites) over an extended period of time. Generalizability can be improved by replicating and comparing the analysis in other case sites in a multiple case design.
Focus Group Research - a type of research that involves bringing in a small group of subjects (typically 6-10 people) at one location, and having them discuss a phenomenon of interest for a period of 1.5-2 hours.
Action Research - assumes that complex social phenomena are best understood by introducing interventions/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.