Types of Research and Designs
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Transcript of Types of Research and Designs
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Types of Research and Designs
• This week and next week…• Covering
– Research classifications– Variables– Steps in Experimental Research– Validity– Research Designs– Common Sources of Error
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RESEARCH DESIGNS
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Types of Designs
• Research designs are ways to structure and conduct research in order to avoid the threats to internal and external validity.– Pre-experimental designs– True experimental designs– Quasi-experimental designs
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Pre-experimental Designs
• Fewest controls– No random sampling– No random assignments– Controls few threats to validity
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True Experimental Designs
• Most controls– Random sampling– Random assignments– All threats to internal validity controlled
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Quasi-experimental Designs
• Some controls– (maybe) random sampling– (maybe) random assignments– Not all threats to internal validity controlled,
but attempts are made to control some of them.
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Types of Designs
• Research designs are ways to structure and conduct research in order to avoid the threats to internal and external validity.– Pre-experimental designs– True experimental designs– Quasi-experimental designs
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Design Complexity
• X = treatment administered• O = data collected• Example:
– O1 – X – O2
– Pre-test vs. post-test design
– Look at Table 7.2…
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Methods of Control
• Physical manipulation– Researcher controls all aspects
• Selective manipulation– Selecting certain participants controls threats to
internal and external validity1. Matched pairs and block designs
• Participants with similar scores on a dependent variable are matched into pairs (for two groups) or into blocks if more than two groups are needed.
• The participants are still randomly assigned to the treatment groups
• This procedure allows comparisons between or among groups that started equally
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Methods of Control
2. Counterbalanced design– All participants receive all treatments, but in
random order– Example:
– Sarah?
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Methods of Control2. Statistical techniques
– When physical and selective manipulations of variables cannot be accomplished
– Groups differ on a known variable, but you can’t do anything about it in terms of the design
– There are many ways to statistically control for these differences– ANCOVA (analysis of covariance)
– Adjusts the differences among groups (variates) based on the common variability in one variable (the covariate)
– Normalization– A technique that is commonly used to reduce between-
subject and between-group variability– Limited to looking at the “patterns” in the data
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COMMON SOURCES OF ERROR
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Common Sources of Error
• Hawthorne Effect• Placebo Effect• “John Henry” Effect• Rating Effect• Experimenter Bias Effect• Participant-Researcher Interaction Effect• Post Hoc Error
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Hawthorne Effect
• Named after a study conducted at the Hawthorne Electric Plant in the 1920’s.– It was observed that a group of workers that
participated in the study acted differently because they “felt special.”
– Therefore, participants should…• Be unaware that they are participating in a study• Be unaware of the hypotheses being tested
– Within the confines of human subject research restrictions
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Placebo Effect
• If participants believe that a change is supposed to occur as a result of a treatment, they will respond with a change in performance (no matter what the treatment is).– Therefore, participants should…
• Be randomly assigned to treatment and placebo groups
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“John Henry” Effect
• Participants know that they are in a control group and that the experimental group is supposed to be better, therefore, the control group tries harder to outperform the experimental group.– Therefore, participants should…
• Not be aware of the group they are in– If they all think they are in a control group, they will all try
hard.
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Rating Effect
• Several kinds of rating effects:– Halo effect:
• The tendency to let initial impressions or ratings of a participant or group influence future ratings.
– Over-rater/under-rater error• When researchers tend to over- or under-rate
subjects– Central tendency error
• When researchers rate subjects toward the middle of the scale
• When subjects rate issues toward the middle of the scale
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Experimental Bias Effect
• The bias of a researcher can effect the outcome of a study.– Therefore, studies should be blinded.
• Single blinded studies– Only the subjects are blinded to the treatments
• Double blinded studies– Subjects and investigators blinded to the treatments
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Participant-Researcher Interaction Effect
• How participants respond to different researchers.– Sometimes, males and females respond
differently to male vs. female researchers.• Therefore, researchers should…
– Act and respond to subjects exactly the same way each time (professionally)
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Post Hoc Error
• Error that is introduced by assuming a cause-and-effect relationship between two variables– Example:
• More people die in a bed than any other place; therefore, beds are dangerous.
– Therefore, researchers should…• Not assume cause-and-effect relationships without
sufficient evidence