Chapter 6: Validity Flashcards
internal validity:
Extent to which you are able to say that no other variable except the one you are studying caused the result
What is meant by confounding?
When some condition co-varies with the independent variable in such a way that their separate effects cannot be sorted out, the two variables are confounded
Why is confounding particularly acute in research in which a subject variable is used?
- Who are smarter men or women - these are the subjects and selected not controlled
- Problem is there are so many reasons why a woman or man might be smarter based on confounding variables that are not related to gender even
- Same problem when correlating race with IQ
construct validity:
extent to which the results support the theory behind the research
- It looks like the guy giving the homeless man a $1 is empathetic so we can measure the construct of empathy through the action
- But what is he gives him a $1 to impress his girlfriend, then our construct validity is off, so measuring constructs is hard to do
How can you ensure construct validity?
Actually, you cannot, but you can plan your research so that it is more plausible.
Construct validity is similar to internal validity in what way?
In internal validity, you strive to rule out alternative variables as potential causes of the behavior of interest; in construct validity, you must rule out other possible theoretical explanations of the results.
external validity:
how well the findings of an experiment generalize to other situations or populations
- Example in book:
- Ask people in 1949 to say rape and they have a hard time so they delay
- Ask people in 2017 to do the same and no taboo no problem, so the experiment in 1949 lacks external validity in that it cannot be generalized to today’s population
ecological validity:
extent to which an experimental situation mimics a realworld situation
- Example in book:
- They’d have to read the words forma story to mimic a real life situation using swear words
- context
statistical conclusion validity:
extent to which data are shown to be the result of cause-effect relationships rather than accident
- It also asks how strong the relationship is between the independent and dependent variables
- you must be certain that you have tested enough people, so that your statistical test will have adequate power
- there is still a chance that it might instead be the result of random error in sampling or measurement.
- there is no way to guarantee any of the types of validity of a research result; all methods of judging validity simply increase confidence in the conclusion that has been drawn from research.
Briefly describe the major threats to internal validity
1) ambiguous temporal precedence: although two variables are related, it is not clear which one is the cause and which one is the effect
- Hard to know if poverty = poor level of performance in school because poverty came first
- If doing poorly in school caused your kids to be poor then it’s the counterintuitive version so it’s an ambiguous chicken egg
2) history: events that occur outside of the experiment that could influence the results of the experiment
- I walk into a study on the effect of giving me a muffin on my happiness on monday and no muffin on Wednesday
- My girlfriend dumped me on Monday, so history, confounds the results and the effect of the muffin
3) maturation: a source of error in an experiment related to the amount of time between measurements
- Happens in longitudinal studies
4) effect of repeat testing: performance on a second test is influenced by simply having taken a first test
- later behavior is changed by the earlier experience.
- Similar to maturation but the change is caused by the testing procedure itself, rather than by processes unrelated to the test
regression effect:
tendency of subjects with extreme scores on a first measure to score closer to the mean on a second testing (regression to the mean)
The more people you have the less likely it is that regression to the mean will negatively effect your results
random error:
that part of the value of a variable that can be attributed to chance
corrected by the regression to the mean concept
Mortality
(selective subject loss or attrition): the dropping out of some subjects before an experiment is completed, causing a threat to validity
is a threat to validity because the participants who drop out of a study may be different from those who complete it. Biases can result if particular kinds of participants drop out.
Not necessarily death
Briefly describe two threats to construct validity
- Loose Connection Between Theory and Method
- Hard to tell what motivated the guy who gave the homeless person $1
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- Hard to tell what motivated the guy who gave the homeless person $1
- Ambiguous Effect of Independent Variables
Whenever people are aware that they are participating in an experiment, their behavior may be different from their everyday behavior.
Briefly describe three threats to external validity
- Other Subjects
- If you are doing an experiment with college students on bargaining and negotiation, will the results validly pre- dict what a secretary of state or a general would do?
- Other Times
- Asking people about gay population 40 years ago would be different and not generalize to today’s population
- Other settings
- Though laboratory research ensures a higher level of control, it is sometimes not easy to decide if a certain effect is simply a laboratory effect or whether it would survive transplantation to the world outside the laboratory