1. Quantitative Research

2. Overview Non-experimental QualitativeCase study Phenomenology Ethnography Historical Literature Review QuantitativeObservational Survey Archival Meta-analysis ExperimentalExperiment Quasi-experiment

3. Observational Definition - Directly observing naturally occurring behavior unobtrusively, typically in the field, but can also take place in laboratory settings Pros -Goal is unobtrusive observation so that your presence does not alter the participant’s affect, behavior, cognition -Allows for continuous measurement -Avoid participant self report error Other -Construct Validity – depends on usage -External Validity – Excellent b/c naturally occurring -Bias – coding bias -Error – coding errors

4. Observational Choose “Observational” if… -interested in naturally occurring behavior -interested in studying a phenomenon as it is naturally occurring -interested in gathering information about naturally occurring boundary conditions or moderators -interested in depth/breadth of continuous measurement

5. Survey Definition -Using self-report measures in any type of collection method --- ► in-person, online, telephone, and mail Pros -Relatively easy to collect data -Multiple collection methods for larger and representative sample sizes Other -Construct – depends on usage -External – excellent because large sample sizes and representative samples -Bias – social desirability bias (except online) -Error – participant self-report error

6. Survey Choose “Survey” if… -your topic can be analyzed using self- report -interested in collecting a lot of data – many variables and questions -interesting in collecting a lot of data – many subjects, power -interested in representative sample and generalizability -have little money, time, resources (except for mail/telephone if using Survey Company)

7. Archival Definition - Using previously collected materials to analyze new research questions by using quantitative (numbers) analysis Pros -No longer restricted only to present-day people and events so access to larger sets of data -Unobtrusive so reduced chances of experimenter error Other -Construct – Insensitive measures since not collected for purpose of your study, No control over how information collected so possibly flawed -External – depends on inclusion criteria -Bias – coding bias -Error – coding error

8. Archival Choose “Archival” if… -Same as with “Historical”, such as interested in origins and growth interested in particular historical events no current data on point so look to past data want to “generalize” from past events to current or future events research question can only be answered by previously collected data -Plus… have resources like coders, time want to minimize experimenter bias want to synthesize and compare data quantitatively

9. Meta-analysis Definition - A meta-analysis statistically combines the results of several studies that address a shared research hypotheses Pros -Central tendency - whether X affects Y, is the effect significant, and how strong is that effect? -Variability - If there is heterogeneity, then look for moderating variables that explain the variability. Does the effect of X on Y differ with moderator? Other -Construct – Depends on CV of included works -External – Depends on EV of included works -Bias – Inclusion/Exclusion bias, Interpretation bias -Errors – Inclusion/Exclusion error

10. Meta-analysis Choose “Meta-analysis” if… -Same as with “Literature Review”, such as have an argument that can be supported by published research interested in “summarizing” the literature for a variety of reasons interested in in “interpreting” the literature, for a variety of reasons interested in communicating the “quality” of the literature, for a variety of reasons -Plus… have resources like coders, time want to minimize experimenter bias want to synthesize and compare data quantitatively

11. Meta-analysis What are those “reasons”? -Same as “Literature Review”, such as No one has previously summarized and/or interpreted the primary articles The literature has grown to the point that it necessitates guidance or direction There is a new topic that cross-cuts many previous literatures so new Literature Review needed to synthesize disparate literature relevant to new topic There are controversies or disagreements that need resolution or support from summarizing/interpreting the literature -Plus… Interested in “overall effect” of literature There are new/old “moderators” that you want to test and/or can be tested across studies

12. Experiment Definition -Testing cause-and-effect relationships by: (1) random assignment of Ss (2) to two or more conditions (3) which differ in terms of (only) IVs Pros -Can prove causation -Tight controls Other -Construct – depends on usage -External – experiments are artificial; alternative is conduct field study but then problem is loss of control and influence of extraneous variables - Internal – see the information from the previous PowerPoint slides about internal validity -Bias – experimenter bias -Error – experimenter error

13. Experiment Choose “Experiment” if… -want to prove causation

14. Quasi-Experiment Definition -Contains aspects of both experiments and non- experiments because deficient in at least one of the three aspects of experimental designs Pros -Depends on which aspects of experiment and which aspects of non-experiment are involved in the quasi-experiment Other -Construct – depends on… -External – depends on… -Bias – depends on… -Error – depends on…

15. Quasi-Experiment Choose “Quasi-Experiment” if… -want scientific rigor of experiments but can’t satisfy all three requirements for variety of reasons (see next PowerPoint presentation about all the types of quasi- experiments such as hybrid, matched- pairs, within-subjects, mixed-designs, and single-n studies

16. Advanced Sources Observational Participant Observation: A Methodology for Human Studies, by Jorgensen, Sage Publications Survey Chapter 9 (Survey Research) of The Handbook of Research Methods in Social and Personality Psychology, Edited by Reis and Judd Archival Archival Strategies and Techniques, by Hill Meta-analysis Practical Meta-analysis, by Lipsey and Wilson Experiment and Quasi-experiment Experimental And Quasi-experimental Designs For Research, by Campbell Experimental and Quasi-Experimental Designs for Generalized Causal Inference, by Shadish et al