Research Methods

Research Methods

Validity • internal validity • extent to which results (differences in DV) can be attributed to IV • must try to eliminate confounds: any factor occurring in a study that makes the results uninterpretable; anything other than the IV that might influence the DV • external validity • extent to which results are generalizable outside the laboratory

Case Study • in depth observation of single individual • problems • no control for bias or error on the part of the observer • don’t know the extent to which that individual is representative of the larger population (can’t generalize) • can be source of hypotheses

Correlational Research • changes in one variable are associated with changes in a second variable • correlation coefficient • Ranges from -1 to 1 • indicates the strength and direction of relationship • can’t make causal interpretations • “third-variable” problem

Experimental Research • IV vs. DV • experimental group vs. control group • importance of random assignment to condition • helps to reduce the effect of confounding variables • issue of placebo effects • occurs when the subject experiences some change or effect simply because he/she expects to

Experimental Research (continued) • issue of experimenter effects • occurs when the experimenter biases the outcome • example: allegiance effect • double-blind strategies • neither the researcher nor the subjects know which subjects are in the experimental group and which subjects are in the control group

Quasi-experimental Research • don’t actually manipulate IV • take advantage of naturally occurring differences in subjects’ exposure to IV • don’t randomly assign subjects to condition • thus, there may be confounding variables present • makes causal interpretations more difficult

Single-Case Experimental Designs • systematic study of one individual under a variety of experimental conditions • researcher manipulates the IV in ways that reduce the likelihood of confounding explanations • differ from case studies in the use of various strategies to improve validity, thereby reducing the number of confounding variables

Single-Case Experimental Designs • Repeated measurements: • behavior (DV) is measured several times before you manipulate IV and afterward • example: • measure the number of tantrums (DV) on each day for 7 days • begin implementing time-out (IV) • measure the number of tantrums (DV) on each day for 7 more days

Single-Case Experimental Designs (continued) • Withdrawal designs: • first, establish baseline of DV • second, manipulate IV and measure DV • third, withdraw IV and measure DV. • example: • have person rate anxiety on 1-10 scale for 2 weeks • give benzodiazepine: have person start taking the benzodiazepine and rate anxiety for 2 weeks while on benzodiazepine • withdraw benzodiazepine; have person stop taking the benzodiazepine and rate anxiety for another 2 weeks

Single-Case Experimental Designs (continued) • Multiple baseline: • researcher manipulates IV at different times across settings, behaviors, or people. • example: implement time-out (IV) for tantrums (DV#1), then “backtalking” (DV#2), then fighting (DV#3)

Studying Behavior Over Time • Cross sectional designs: • compare members of different age groups on some characteristics • example: measure self-esteem of 3 groups of women, 20-yr-olds, 40-yr-olds, and 60-yr-olds • problem: may have cohort effect (the confounding of age and life experiences)

Studying Behavior Over Time (continued) • Longitudinal designs: • follow one group for extended period of time • example: measure self-esteem among one group of women when they are 20, 40, and 60 years old • problem: may have subject attrition • Sequential designs: • repeated study of different cohorts over time • combines features of longitudinal and cross-sectional designs • example: start with 3 groups of women born in 1940, 1960, and 1980. Measure each of them at 20-year follow-up intervals

Studying Genetics • Family studies • Adoption studies • Twin studies

Research Methods