quasi-experiments – outline 1. true experiments a. characteristics b. threats to validity...
TRANSCRIPT
Quasi-Experiments – Outline
1. True Experimentsa. Characteristicsb. Threats to validity controlled by experimentsc. Threats not controlled by experimentsd. Obstacles to true experiments in the field
2. Quasi-experimentsa.The logic of quasi-experiments b.Non-equivalent control group design
• Example – Langer & Rudin (1976)c. Interrupted time-series design
• Example – Campbell (1969)
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True Experiments - Characteristics
• True experiments are characterized by:• A manipulation• A high degree of control• An appropriate comparison
(the major goal of exerting control)
• Manipulation in the presence of control gives you an appropriate comparison.
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Threats to validity controlled by true experiments
• History • occurrence of an event other than the treatment
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Threats to validity controlled by true experiments
• Maturation • participants always change as a function of time. Is change in behavior due to something else?
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Threats to validity controlled by true experiments
• Testing • improvement due to practice on a test (familiarity with procedure, or with testers expectations)
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Threats to validity controlled by true experiments
• Instrumentation • especially if humans are used to assess behavior (fatigue, practice)
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Threats to validity controlled by true experiments
• Regression • when first observation is extreme, next one is likely to be closer to the mean.
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Threats to validity controlled by true experiments
• Selection • if differences between groups exist from the outset of a study
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Threats to validity controlled by true experiments
• Mortality • if exit from a study is not random, groups may end up very different
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Threats to validity controlled by true experiments
• Interactions of selection… • with History• with Maturation• with Instrumentation (ceiling
effects)
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Note difference between these threats:
• Maturation• One group; performance
better on post-test than on pre-test
• Interaction of Maturation & Selection• Two or more groups• Performance difference
larger on post-test than on pre-test
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Threats to validity not controlled by experiments
• Contamination• communication of
information about the experiment between groups of subjects
• Cook & Campbell (1979):• resentment• ‘compensatory rivalry’• diffusion of treatment:
control subjects use information given to others to change their own behavior.
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Contamination – an example
• Craven, Marsh, Debus, & Jayasinghe (2001)
• Journal of Educational Psychology
• Teachers trained to improve students’ academic self-concept through praise
• Internal control• External control
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Contamination – an example
• Craven, Marsh, Debus, & Jayasinghe (2001)
• Next slide shows T2 (post-test) academic self-concept scores as a function of T1 scores for control children only.
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External controlInternal control
Internal high focusInternal low focus
1.0
0.5
0.0
-0.5
-1.0Low Medium High T1 acad self concept
Diffusion
No diffusion
T2 acad self concept
Low focus group consistently higher than external control
Resentful demoralization?Overzealous cooperation?
Threats to validity not controlled by experiments
• Threats to external validity • best way to deal with this is replication
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Threats to validity not controlled by experiments
• Hawthorne effects • changes in a person’s behavior due to being studied rather than the manipulation.
• a special kind of reactivity.
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Hawthorne effects
• Demand characteristics • cues communicated by researcher
• subject’s under-standing of their role
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Hawthorne effects
• Role of “research subject” • Is subject behaving the way he thinks a person in that role should behave?
• (E.g., hypnotized person)
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Hawthorne effects
• Orne (1962) • ‘good subjects’ think they are contributing to science by complying with researcher’s demands
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Hawthorne effects
• What to do about Hawthorne effects?
• Orne (1962): Use quasi-control subjects as “co-investigators”
• They do your task, reflect on demand characteristics of the experiment.
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Obstacles to true experiments in the field
• Sometimes, we cannot bring the phenomenon we want to study into the lab, so we have to work in the field.
• Can we do experiments in the field?
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Obstacles to true experiments in the field
• Can’t get permission from individuals in authority?
• Your study may involve some time and effort on their part. But what’s in it for them?
• In schools, parents also have to agree.
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Obstacles to true experiments in the field
• Can’t assign subjects to groups randomly?
• have to work with intact groups (e.g., classes in a school)
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Quasi-Experiments
• Quasi-experiments resemble true experiments… • usually include a
manipulation, and provide a comparison.
• …but they are not true experiments.• lack high degree of control
that is characteristic of true experiments.
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Quasi-Experiments
• Quasi-Experiments are compromises
• They allow the researcher some control when full control is not possible.
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Quasi-Experiments
• Because full control is not possible, there may be several “rival hypotheses” competing as accounts of any change in behavior observed.
• How do we convince others that our hypothesis is the right one?
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The Logic of Quasi-Experiments
• Eliminate any threats you can• Show how each threat to
validity on list given above is dealt with in your study.
• Argue that others don’t apply.• using evidence or logic
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Two kinds of quasi-experiments
• Non-equivalent control group
• “non-equivalent” because not randomly assigned
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Two kinds of quasi-experiments
• Interrupted time-series design
• a series of observations over time, interrupted by some treatment
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Non-equivalent Control Group design
• Control group is “like” the treatment group.
• Chosen from same population
• Pre- and post-test measures obtained for both groups, so similarity can be assessed.
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Non-equivalent Control Group design
• Control group is not equivalent
• subjects are not randomly-assigned to control & treatment groups
• so best you can do is argue that comparison is appropriate.
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Non-equivalent Control Group design
• If the groups are comparable to begin with, this design potentially eliminates threats to internal validity due to:
• History• Maturation• Testing• Instrumentation• Regression
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Problems with the NECG design
• Threats to validity due to interactions with selection may not be eliminated using the NECG design.
• Selection and maturation
• Most likely when treatment group is self-selected (as in psychotherapy cases – people who sought help).
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Problems with the NECG design
• Selection and history • Does one group experience some event that has a positive or negative effect (e.g., teacher of one class leaves)?
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Problems with the NECG design
• Selection and instrumentation
• Does one group show ceiling or floor effects?
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Problems with the NECG design
• Regression to the mean • Are one group’s pretest scores more extreme than the other group’s?
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Possible NECG study outcomes
• both experimental and control groups show improve-ment from pretest to posttest
• appears not to be any effect of the treatment
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Pretest Posttest
Control group
Possible NECG study outcomes
• Looks like a treatment effect, but there may be a threat due to• selection and maturation, • selection and history
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Pretest Posttest
Control group
Possible NECG study outcomes
• Selection and maturation could be a threat
• Or interaction of selection and • history• testing• instrumentation• or mortality.
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Pretest Posttest
Control group
Possible NECG study outcomes
• Interaction of selection and regression looks like a serious threat here
• Selection and maturation probably not a threat here.
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Pretest Posttest
Possible NECG study outcomes
• Crossover effect• Clearest evidence for an
effect of the program of any of these graphs.
• Selection and instrumentation not a problem – no ceiling or floor effects
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Pretest Posttest
Quasi-experiment example
• Langer & Rudin (1976)• Research conducted in
retirement home.
• Residents on one floor given more control over their daily lives
• Residents of another floor given same interaction with staff, but no increased control.
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Langer & Rudin (1976) – Measures
• Ratings• Self-report of feeling of
control from residents• Staff assessments of mental &
physical well-being, by ‘blind’ assessors
• Objective measures • record of movie attendance• participation in “Guess how
many jelly-beans” contest on each floor
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L & R (1976) – limits on control
• L & R had no control over • who entered the home• who was assigned to either
floor.• no control over staff hiring
or firing / resigning.
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L & R (1976) – Possible Problems
• Interaction of Selection and Maturation• even if groups have similar
pretest scores, they may differ on things pretest didn’t measure
• probably not a problem here – people on both floors had similar SES
• assigned to floors randomly, not by health status.
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L & R (1976) – Possible Problems
• Selection and history • suppose a popular (or unpopular) nurse left one of the floors during the study. That might influence well-being.
• L & R did not address this issue.
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L & R (1976) – Possible Problems
• Selection and instrumentation
• did one group show ceiling or floor effects?
• L & R say, no.
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L & R (1976) – Possible Problems
• Regression • were one group’s pretest scores more extreme than the others?
• L & R say, no.
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L & R (1976) – Possible Problems
• Observer bias and Contamination
• observers in the L & R study were not aware of the hypothesis.
• L & R reported there was little communication between floors.
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L & R (1976) – Possible Problems
• Hawthorne Effect • cannot be ruled out, but L & R took care to give both floors same attention.
• Message varied between floors, but “face time” was the same.
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L & R (1976) – Possible Problems
• External Validity • might be an issue. • home involved was rated
“one of the finest” in the state
• subjects may have been atypical in their desire for control
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Two kinds of quasi-experiments
• Non-equivalent control group
• Interrupted time-series design
• a series of observations over time, interrupted by some treatment
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Time-Series Designs
• In T-S designs, performance is measured both before and after a treatment.
• If there is an abrupt change in performance at time of treatment, we conclude that treatment worked.
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Time-series designs example
• Campbell (1969)• Effect of speed limit
reduction on traffic fatalities in Connecticut
• incidence of traffic fatalities in years before and after the speed limit reduction,
• conclusion: speed limit change had a modest effect.
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Campbell (1969)
• Any threat to internal validity?
• other explanations for any change in traffic fatality incidence:• Changes in car safety• Weather• Record keeping
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Campbell (1969)
• Any threat to internal validity?
• Such effects should be similar in neighboring states
• Campbell found no change in fatality incidence in those states.
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Campbell (1969)
• Any threat to external validity?
• E.g., would treatment have same effect in other states, or are people in Connecticut more law-abiding?
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