Research Design

Descriptive (“what”) –No attempt to develop a hypothesis –Example: Where do guns used in crime come from? Explanatory (“why”) –Hypothesis (poverty causes crime) Exploratory –Purpose to find out enough about a topic to properly frame “why” –Usually includes an “implicit” hypothesis Unit of analysis: “object, entity or process” under study –Contains the variables being measured –Case: A single instance of a unit of analysis Types of Research

Research design: Experimental Purposes –Eliminate other possible “causes” Automatically control for other independent variables –Assure causal order – that cause precedes effect Method –Randomly assign cases to two or more groups –Pre-measure independent and dependent variables –Designate one or more groups as “experimental” and one or more as “control” –Intervene (e.g., introduce independent variable or adjust level of existing independent variable in the hypothesized direction) –Post-measure dependent variable. Any substantial difference between the experimental and control groups can be attributed to the intervention

Simple experiment ( X ) DV t1 …IV….DV t2 (intervention) ( C ) DV t1 …..……DV t2 (no intervention) Solomon four-group design (checks for effects of premeasure) X 1 DV t1 … IV … DV t2 C 1 DV t1 ………… DV t2 X 2 ………. IV … DV t2 C 2 ……………… DV t2

No random assignment to groups and/or No control group Issues Without random assignment, groups might differ in an important respect. –“Matching” sometimes used Without a control group, an extraneous event (“maturation effect”) might have caused the change in the level of the dependent variable. Research design: Quasi-experimental

Causal order: Did the change in the independent variable precede the change in the dependent variable? Poverty  Crime ? Crime  Poverty ? Intervening variables: Could lack of education or living in a violent area be the true cause of crime? Poverty  poor education  crime Spurious relationships (lunar cycles and homicide) Ethical and practical constraints of doing research Research design: Non-experimental

Simple non-experimental: Retrospectively measure independent and dependent variables Poverty  Crime Cross-sectional –If a simple comparison is desired, can create subgroups that share the same value for a variable of choice (e.g., gender) Subgroup 1 - male Subgroup 2 - female –If the the subgroups score differently on the variable(s) being measured, can we suggest why? “After-only”: measure only after an intervention has occurred Release placement  recidivism

Panel designs –Longitudinal: repeatedly measuring one or more variables for the same group over time T(time)1 => T2 => T3 => T4 –Multiple group trend: measure different subset of the original group on each occasion Group 1 T1 Group 2 T2 Group 3 T3 Group 4T4 –Why?