NonExperimental designs Psych 231 Research Methods in Psychology

Non-Experimental designs Psych 231: Research Methods in Psychology

n Quiz 9 (chapters 12 & 13) is due on Nov. 5 th (Wed) at midnight Reminders

n Sometimes you just can’t perform a fully controlled experiment n n Because of the issue of interest Limited resources (not enough subjects, observations are too costly, etc). • Surveys • Correlational • Quasi-Experiments • Developmental designs • Small-N designs n This does NOT imply that they are bad designs n Just remember the advantages and disadvantages of each Non-Experimental designs

n Used to study changes in behavior that occur as a function of age changes n n Age typically serves as a quasi-independent variable Three major types n n n Cross-sectional Longitudinal Cohort-sequential Developmental designs Video lecture (~10 mins)

n Cross-sectional design n Groups are pre-defined on the basis of a preexisting variable • Study groups of individuals of different ages at the same time • Use age to assign participants to group • Age is subject variable treated as a between-subjects variable Age 4 Age 7 Age 11 Developmental designs

n Cross-sectional design n Advantages: • • Can gather data about different groups (i. e. , ages) at the same time Participants are not required to commit for an extended period of time Developmental designs

n Cross-sectional design n Disadvantages: • Individuals are not followed over time • Cohort (or generation) effect: individuals of different ages may be inherently different due to factors in the environment • • • Are 5 year olds different from 15 year olds just because of age, or can factors present in their environment contribute to the differences? • Imagine a 15 yr old saying “back when I was 5 I didn’t have a Wii, my own cell phone, or a netbook” Does not reveal development of any particular individuals Cannot infer causality due to lack of control Developmental designs

n Longitudinal design n Follow the same individual or group over time • Age is treated as a within-subjects variable • • Rather than comparing groups, the same individuals are compared to themselves at different times Changes in dependent variable likely to reflect changes due to aging process • Changes in performance are compared on an individual basis and overall time Age 11 Age 15 Age 20 Developmental designs

n Example n Wisconsin Longitudinal Study (WLS) • Began in 1957 and is still on-going (50 years) • 10, 317 men and women who graduated from Wisconsin high schools in 1957 (and randomly selected brothers and sisters, and spouses too) • Originally studied plans for college after graduation • Now it can be used as a test of aging and maturation • Data collected in: • 1957, 1964, 1975, 1992, 2004, 2011 Longitudinal Designs

n Longitudinal design n Advantages: • Can see developmental changes clearly • Can measure differences within individuals • Avoid some cohort effects (participants are all from same generation, so changes are more likely to be due to aging) Developmental designs

n Longitudinal design n Disadvantages • Can be very time-consuming • Can have cross-generational effects: n n Baby boomers Generation X Mellennials Generation Z • Conclusions based on members of one generation may not apply to other generations • Numerous threats to internal validity: • Attrition/mortality • History • Practice effects • Improved performance over multiple tests may be due to practice taking the test • Cannot determine causality Developmental designs

n Cohort-sequential design n Measure groups of participants as they age • Example: measure a group of 5 year olds, then the same group 10 years later, as well as another group of 5 year olds n Age is both between and within subjects variable • Combines elements of cross-sectional and longitudinal designs • Addresses some of the concerns raised by other designs • For example, allows to evaluate the contribution of cohort effects Developmental designs

n Cohort-sequential design Cross-sectional component Time of measurement 1975 Cohort A 1970 s Cohort B 1980 s Cohort C 1990 s Age 5 1985 1995 Age 15 Age 25 Age 15 Age 5 Longitudinal component Developmental designs

n Cohort-sequential design n Advantages: • Get more information • Can track developmental changes to individuals • Can compare different ages at a single time • Can measure generation effect • Less time-consuming than longitudinal (maybe) n Disadvantages: • Still time-consuming • Need lots of groups of participants • Still cannot make causal claims Developmental designs

n Sometimes you just can’t perform a fully controlled experiment n n Because of the issue of interest Limited resources (not enough subjects, observations are too costly, etc). • Surveys • Correlational • Quasi-Experiments • Developmental designs • Small-N designs n This does NOT imply that they are bad designs n Just remember the advantages and disadvantages of each Non-Experimental designs

n What are they? n n Historically, these were the typical kind of design used until 1920’s when there was a shift to using larger sample sizes Even today, in some sub-areas, using small N designs is common place • (e. g. , psychophysics, clinical settings, animal studies, expertise, etc. ) Small N designs

n In contrast to Large N-designs (comparing aggregated performance of large groups of participants) n One or a few participants Data are typically not analyzed statistically; rather rely on visual interpretation of the data n Small N designs

= observation Steady state (baseline) Treatment introduced n n Observations begin in the absence of treatment (BASELINE) Then treatment is implemented and changes in frequency, magnitude, or intensity of behavior are recorded Small N designs

= observation Transition steady state Steady state (baseline) Treatment introduced n Treatment removed Reversibility Baseline experiments – the basic idea is to show: 1. when the IV occurs, you get the effect 2. when the IV doesn’t occur, you don’t get the effect (reversibility) Small N designs

Unstable § Stable Before introducing treatment (IV), baseline needs to be stable Measure level and trend § n Level – how frequent (how intense) is behavior? • Are all the data points high or low? n Trend – does behavior seem to increase (or decrease) • Are data points “flat” or on a slope? Small N designs

Steady state (baseline) Transition steady state n Reversibility ABA design (baseline, treatment, baseline) – The reversibility is necessary, otherwise something else may have caused the effect other than the IV (e. g. , history, maturation, etc. ) n There are other designs as well (e. g. , ABAB see figure 13. 6 in your textbook) ABA design

n Advantages n n n Focus on individual performance, not fooled by group averaging effects Focus is on big effects (small effects typically can’t be seen without using large groups) Avoid some ethical problems – e. g. , with nontreatments Allows to look at unusual (and rare) types of subjects (e. g. , case studies of amnesics, experts vs. novices) Often used to supplement large N studies, with more observations on fewer subjects Small N designs

n Disadvantages n n n Difficult to determine how generalizable the effects are Effects may be small relative to variability of situation so NEED more observation Some effects are by definition between subjects • Treatment leads to a lasting change, so you don’t get reversals Small N designs

n n Some researchers have argued that Small N designs are the best way to go. The goal of psychology is to describe behavior of an individual Looking at data collapsed over groups “looks” in the wrong place Need to look at the data at the level of the individual Small N designs