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38 Cards in this Set
- Front
- Back
What two things do experimenters do to enhance/protect construct validity? |
1. Manipulation check 2. Pilot study |
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What is a manipulation check? |
A test used to determine the effectiveness of a manipulation in an experimental design. |
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What is a pilot study? |
A small study designed to gather information prior to a larger study, in order to improve the quality of a larger study. (Shorter; cheaper) (Can be considered a "mini-experiment".) |
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What do you have to make sure of when gathering participants for a pilot study? |
That they're from the same population. |
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What is external validity? |
The degree to which findings generalize to:
*Other groups *Other situations/contexts Ex.; The fact that the participants of Dr. Schwartz's studies are primarily UTEP students raises the question asking whether her findings generalize to the entire population. |
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What is conducted to assess external validity? |
Replication studies |
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What is observation bias? |
When an experimenter's expectation influences the interpretation (interpretation of patterns of dependent variable) of the results. |
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What major thing tends to cause observation bias experimenters? |
Open-ended questions |
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One group, pretest/posttest design |
Design in which a researcher recruits one group of participants, measures them on a pretest, exposes them to a treatment or change, and then measures them on a posttest; an ineffective experimental design |
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Maturation |
A change in behavior that emerges more or less spontaneously over time through natural development or spontaneous improvement; e.g. people slowly adapt to strange environments, children get better at walking and talking, plants get taller without any outside help |
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Spontaneous remission |
Phenomenon that occurs when the symptoms of depression or other disorders get better, for no known cause, with time |
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History threat |
Threat to internal validity that occurs when a "historical" or external event occurs to everyone in the treatment group at the same time as treatment, so it is unclear whether the change in the experimental group group is caused by the treatment received or by the historical event |
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Regression threat |
Threat caused by a statistical concept called regression toward the mean; when a performance is extreme at time 1, at time 2 it is likely to be closer to a typical, or average, performance |
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Attrition |
Occurs when people drop out of the study before it ends; aka "mortality" |
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Testing effect |
A type of order effect in which scores change over time just because participants have taken the test more than once |
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Instrumentation threat |
Threat that occurs when a measuring instrument changes over time from having been used before; aka instrument decay |
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Demand characteristics |
A problem when participants guess what the study is supposed to be about and change their behavior in the expected direction |
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Double-blind study |
Study in which neither the participants nor the researchers who evaluate them know who is in the treatment group and who is in the comparison group |
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Design confound |
When a second variable unintentionally varies systematically with the independent variable |
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Selection effect |
In an independent-groups design, when the two independent variable groups have systematically different kinds of participants in them |
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Order effect |
In a within-groups design, when the effect of the independent variable is confounded with practice, fatigue, boredom, or carryover from one level to the other |
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Regression to the mean |
An experimental group whose score is extreme at pretest will get better (or worse) over time, because many random events that caused the extreme pretest scores do not recur the same way at posttest |
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Observer bias |
An experimental group's ratings differ from a comparison group's, but only because the researcher expects the group's ratings to differ |
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Placebo effect |
Participants in an experimental group improve only because they believe in the efficacy of the therapy or drug they receive |
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Null effect |
Finding that the independent variable did not make a difference in the dependent variable; no significant correlation between two variables |
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Weak manipulations |
Changes in the independent variable that are not significant enough to affect the dependent variable |
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Ceiling effect |
Special cases of weak manipulations or insensitive measures that cause independent variable groups to all score at the high end |
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Floor effect |
Special cases of weak manipulations or insensitive measures that cause independent variable groups to all score at the low end |
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Measurement error |
Factors that can inflate or deflate a person's true score on a dependent measure |
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Situation noise |
A third factor that could cause variability within-groups and obscure true group differences |
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Which kind of variability is random and, hence, does not threaten internal validity? |
Unsystematic variability |
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Matched-groups design |
An experimental design in which participants who are similar on some measured variable are grouped into sets, then the members of each matched set are randomly assigned to different experimental conditions |
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Between-groups design/independent-groups design |
An experimental design in which different groups of participants are placed into different levels of the independent variable |
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Within-groups design |
An experimental design in which there is only a single group of participants, and each participant is presented with all levels of the independent variable |
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Posttest-only design |
An experimental design in which participants are randomly assigned to independent variable groups and are tested on the dependent variable once |
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Pretest/posttest design |
An experimental design in which participants are randomly assigned to at least two groups and are tested on the key dependent variable twice-once before exposure to the independent variable, and once after exposure |
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Concurrent-measures design |
A within-groups design in which participants are exposed to all the levels of an independent variable at roughly the same time, and a single attitudinal or behavioral preference is the dependent measure |
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Repeated-measures design |
A within-groups design in which participants are measured on a dependent variable more than once, after exposure to each level of the independent variable |