experimental and quasi- experimental designs chapters 9 & 10
TRANSCRIPT
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Experimental and Quasi-Experimental Designs
Chapters 9 & 10
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Research Design It is the outline, plan, or strategy
for the procedures you will use to address your research question.
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Research Designs – What are some limitations of these?
1. One-group after design Treatment Response
measure
2. One-group before-after design Response Measure 1 Treatment Compare Response Measure 2
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Research Designs – What are some limitation of these?
N onequ iva len t posttest-on ly design
R esp on se M easu reC og n it ive F u n c tion in ga t 6 -m on th s fo llow -u p
C ard iac B yp ass &R evascu la riza tion
R esp on se M easu reC og n it ive F u n c tion in ga t 6 -m on th s fo llow -u p
C ard iac R evascu la riza tion
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What are the requirements of true research designs?
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Requirements of True Research Design
Design is adequate to answer the research question (i.e., test the hypothesis).
Control for extraneous variables Results are generalizable.
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Why Pre-testing Your Participants Increased sensitivity of the study Ceiling effect Initial position Initial comparability Evidence of change
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What are the limitations of this design?
True R esearch D esign
R andom ized to :
R esp on seM easu re
D ec is ion a l R eg re t &D is tress
A n xie tyM an ag em en t
R esp on seM easu re
D ec is ion a l R eg re t &D is tress
U su a l C are
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Factorial Design Two or more independent variables
are studied in order to determine their independent and interactive effects on the dependent variable.
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Interaction Effect The effect of one factor
(independent variable) depends on the level of the other factor (other independent variable).
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Main Effects & Interactions
Sad
ness
Sad
ness
Lightness Lightness
Seasonal Affect Disorder
Non-Seasonal Affect Disorder
High High
High HighLow Low
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Advantages of Factorial Designs
More than one hypothesis can be tested.
Potentially confounding variables can be built into the design as factors.
Enables interaction effects to be tested.
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Within Participant After-Only Design
Same research participants in all experimental treatment conditions.
Repeated measures design. Overcomes concerns about creating
equivalence between groups. Requires fewer participants. Most serious limitation is the
confounding influence of a sequence effect.
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Combining Within and Between Participant Designs Factorial design based on a mixed
model. Can include as many independent
variables as is necessary.
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Combining Within and Between Participant Designs
Before - After D esign
P os t-trea tm en tM easu re
E xp erim en ta lG rou p
P os t-trea tm en tM easu re
C on tro lG rou p
R an d om ized to :
P re -trea tm en tM easu res
P artic ip an tsS e lec ted
RepeatedMeasure
Between-SubjectFactor
May want to match beforerandomizing
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Factorial DesignD oes s tress m anagem en t w ork s im ilarly in m edicated and
un m edicated hypertens ives?
P os t m easu rea t 6 -m on th s
B eta B locker &S tress m an ag em en t
P os t m easu rea t 6 -m on th s
B eta B locker, n oS tress m an ag em en t
P os t m easu rea t 6 -m on th s
P laceb o &S tress m an ag em en t
P os t m easu rea t 6 -m on th s
P laceb o , n oS tress m an ag em en t
U n m ed ica ted h yp erten s ivesR an d om ized to :
• Main effect for beta blocker
• Main effect for stress management• Interaction effect for drug and stress management
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Main & Interaction Effects
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Pre Post
Drug & Stress Man. Drug, No Stress Man.Placebo & Stress Man. Placebo, No Stress Man.
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Pre Post
Drug & Stress Man. Drug, No Stress Man.Placebo & Stress Man. Placebo, No Stress Man.
Main Effect Interaction Effect
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Selecting the Appropriate Design
The design must be one that addresses your research question.
What control techniques can and should you apply to help you arrive at an unambiguous answer.
Between or within-in design or mixed model.
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Quasi-Experimental Design
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Quasi-Experimental Does not meet all of the requirements
necessary for controlling the influence of extraneous variables. Most common criteria not met is random
assignment. While you cannot infer cause and effect,
well designed quasi-experiments enable you to demonstrate that rival interpretations are implausible.
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Non -Equivalent Control Group Design: Typical Rival Hypotheses
Increasing treatment effect I outcome
A selection-maturation effect
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Increasing Treatment Effect I Outcome
Pre-test Post-test
Control Group
Experimental Group
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Increasing Treatment and Control Group Outcomes Both groups’ scores increase over
time but one group changes to a greater extent than the other group. Effect could be due to a treatment
effect or to a selection-maturation interaction.
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HADS Depression
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Experimental Control
Time 1Time 2Time 3
ANOVA – time and time by group effect, depressiondecreased in both groups but levelled off in controlGroup at follow-up while continuing to decrease in experimental.
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Increasing Treatment Effect II Outcome
Pre-test Post-test
Control Group
Experimental Group
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Cross-Over Effects
Pre-test Post-test
Control Group
Experimental Group
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Time Series Analyses Useful when you cannot randomize
participants and where it is possible to obtain a series of assessments of the dependent variable at pre-treatment and post-treatment.
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Time Series AnalysisTreatmentApplied
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Classic Studies: Effect of Reduced Speeding on Traffic Accidents in Connecticut
In 1955 there were a record number of traffic accidents ( n = 324) so the Governor (Abraham Ribicoff) introduced a law to reduce the speed limit.
In 1956 there were 284 traffic accidents, a reduction of 12.3%.
Governor concluded that his intervention worked but the effects could just as easily been due to regression to the mean.
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Classic Studies: Effect of Reduced Speeding on Traffic Accidents in Connecticut
Campbell and Ross (1968) used interrupted time series design to test if the reduced trend in traffic accidents was plausible.
Compared traffic accident trend in Connecticut with control States.
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Classic Studies: Effect of Reduced Speeding on Traffic Accidents in Connecticut
‘51 ‘52 ‘53 ‘54 ‘55 ‘56 ‘57 ‘58 ‘59
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Control State
Connecticut
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Class Exercise Specify your research question Your scientific hypothesis Specify your design Break into groups of 5