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NonExperimental designs: Developmental designs

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No labs this week; work on group project data. Journal Summary 2 due in lecture Wed ... Focus on individual performance, not fooled by group averaging effects ... – PowerPoint PPT presentation

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Title: NonExperimental designs: Developmental designs


1
Non-Experimental designs Developmental designs
Small-N designs
  • Psych 231 Research Methods in Psychology

2
Announcements
  • No labs this week work on group project data
  • Journal Summary 2 due in lecture Wed
  • Please write your GAs name on the checklist
  • No names, SSN only

3
Developmental designs
  • Non-experimental or quasi-experimental
  • Used to study changes in behavior that occur as a
    function of age changes

4
Developmental designs
  • Age serves as a quasi-independent variable
  • Three major types
  • Cross-sectional
  • Longitudinal
  • Cohort-sequential

5
Developmental designs
  • Cross-sectional design
  • Study groups of individuals of different ages at
    the same time
  • Group means are then compared

6
Developmental designs
  • Cross-sectional design
  • Groups are pre-defined on the basis of a
    pre-existing variable
  • Use age to assign participants to group
  • Age is subject variable treated as a
    between-subjects variable

7
Developmental designs
  • Cross-sectional design
  • 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

8
Developmental designs
  • Cross-sectional design
  • 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
  • Example are 5 year old different from 13 year
    olds just because of age, or can factors present
    in their environment contribute to the
    differences?
  • Cannot infer causality due to lack of control

9
Developmental designs
  • Longitudinal design
  • Follow the same individual or group over time
  • Repeated measurements over extended period of
    time
  • Age is treated as a within-subjects variable
  • Changes in dependent variable reflect changes due
    to aging process

10
Developmental designs
  • Longitudinal design
  • Rather than comparing groups, the same
    individuals are compared to themselves at
    different times
  • Changes in performance are compared on an
    individual basis and overall

11
Developmental designs
  • Longitudinal design
  • Advantages
  • Can see developmental changes clearly
  • Avoid some cohort effects (participants are all
    from same generation, so changes are more likely
    to be due to aging)
  • Can measure differences within individuals

12
Developmental designs
  • Longitudinal design
  • Disadvantages
  • Can be very time-consuming
  • Can have cross-generational effects
  • Conclusions based on members of one generation
    may not apply to other generations
  • Example are individuals who grew up during WWII
    the same or different from individuals who grew
    up after?

13
Developmental designs
  • Longitudinal design
  • Disadvantages
  • Numerous threats to internal validity
  • Attrition/mortality
  • History
  • Practice effects
  • Improved performance over multiple tests may be
    due to practice taking the test
  • Absence of control
  • Cannot determine causality

14
Developmental designs
  • Cohort-sequential design
  • 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 generation effects

15
Developmental designs
  • Cohort-sequential design
  • Measure groups of participants as they age
  • Example measure a group of 5 year olds, then the
    same group 5 years later, as well as another
    group of 5 year olds
  • Age is both between and within subjects variable

16
Developmental designs
  • Cohort-sequential design
  • Advantages
  • Can measure generation effect
  • Less time-consuming than longitudinal
  • Disadvantages
  • Still time-consuming
  • Still cannot make causal claims

17
Small N designs
  • What are they?
  • Historically, these were the typical kind of
    design used until 1920s 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,
    expertise, etc.)

18
Small N designs
  • One or a few participants
  • Data are not analyzed statistically rather rely
    on visual interpretation of the data
  • Observations begin in the absence of treatment
    (BASELINE)
  • Then treatment is implemented and changes in
    frequency, magnitude, or intensity of behavior
    are recorded

19
Small N designs
  • Baseline experiments the basic idea is to show
  • when the IV occurs, you get the effect
  • when the IV doesnt occur, you dont get the
    effect (reversibility)
  • Before introducing treatment (IV), baseline needs
    to be stable
  • Measure level and trend

20
Small N designs
  • Level how frequent (how intense) is behavior?
  • Are all the data points high or low?
  • Trend does behavior seem to increase (or
    decrease)
  • Are data points flat or on a slope?

21
ABA design
  • 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.)

22
Small N designs
  • Advantages
  • Focus on individual performance, not fooled by
    group averaging effects
  • Focus is on big effects (small effects typically
    cant be seen without using large groups)
  • Avoid some ethical problems e.g., with
    non-treatments
  • 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

23
Small N designs
  • Disadvantages
  • 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 dont
    get reversals
  • Difficult to determine how generalizable the
    effects are

24
Small N designs
  • 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

25
Next time
  • Statistics (Chapter 14)
  • Journal summary due Wed in lecture
  • Put your SSN on checklist the name of your GA
  • No labs this week
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