1. Chapter 10 Finding Relationships Among Variables: Non-Experimental Research

2. Non-experimental research Non-experimental approaches are used when the researcher is unable to control the variables or the nature of the question is not causal. Non-experimental approaches are used when the researcher is unable to control the variables or the nature of the question is not causal. In general, a non-experimental design includes research where: In general, a non-experimental design includes research where: –the researcher does not manipulate an IV, –has limited or no control over the nature or timing of the treatment, or –when causal relationships are not the primary focus of the research.

3. Quasi experiments Quasi experiments Quasi experiments –Designs that look a lot like true experiments and that are statistically analyzed in similar ways. –The researcher can compare groups but does not control the nature and/or the timing of the treatment or comparison variable. Or the treatment may be a participant variable. –Causal interpretations cannot be made. Participant variables – variables associated with the participants themselves (e.g.. gender, a treatment the participant chose). Participant variables – variables associated with the participants themselves (e.g.. gender, a treatment the participant chose).

4. Time series designs Time series design Time series design –A quasi-experimental design where participants who have been exposed to a treatment are tested both before and after the introduction of that treatment. –The researcher does not control the nature of the treatment or the time that it was introduced. –Usually involves several pre and posttest measures and may include a comparison group; both are methods to try to control extraneous variables.

5. Time series designs Interrupted time series design Interrupted time series design –The researcher takes several pretest measures and several posttest measures. –Measuring behavior at different times allows us to determine the natural fluctuation in scores and better assess any post treatment changes. –Because there is no control group, we can’t tell if something else was responsible for the changes in scores (other than the treatment).

6. Time series designs Multiple time series design Multiple time series design –Like an interrupted time series design but includes a control group that was not exposed to the treatment. –Even with a control group be cautious about interpretations. An alternative explanation may explain the outcome (i.e.. the outcome may not have resulted because of the treatment).

7. Non-equivalent groups designs Non-equivalent groups designs Non-equivalent groups designs –Used when researchers want to compare groups that they know, or suspect, are different at the outset of the study. –Compares changes in behavior between the groups. –By comparing changes you control for initial group differences.

8. Longitudinal research Longitudinal research Longitudinal research –Involves studying a group of individuals over a long period of time to determine how characteristics measured earlier in life relate to behavior later in life. –Difficult and expensive to conduct. –Attrition (loss of participants) can be a major problem and may effect the internal validity of the study.

9. Cross-sectional research Cross-sectional research Cross-sectional research –Used to study groups of people who are different ages. –Cohort effect – variables that are confounded with age. Sequential research Sequential research –Combines cross-sectional and longitudinal research by selecting a cross section of ages over a number of years. Cohort effects are controlled by following a number of age cohorts (cross-sectional) over time (longitudinal).

10. Cross-sectional research Microgenetic method Microgenetic method –Involves carefully observing behavior during periods when rapid change is occurring and collecting both quantitative and qualitative information. –Used to study the process of change.

11. Case studies Case studies Case studies –In depth studies of a single individual. –Used when a researcher is interested in studying a single individual on many variables and is not assessing a treatment. –The objective is to describe the characteristics of the individual case, not to generalize to a population of similar cases. –Often qualitative, but can be more quantitative.

12. Correlational research Correlational research Correlational research –Used to study relationships between variables. –Variables that are systematically related are said to be correlated. –Often used to research topics that would otherwise be unethical to study. –Correlation does not infer causation! –Confounding variables may affect the results.

13. Correlational research Multiple regression Multiple regression –A powerful technique that allows us to look at the relationship between a number of predictor variables and a single criterion variable. –Results tell us if the predictor variables are positively or negatively correlated with the criterion variable. Also shows the relative importance of each variable in determining behavior.