Chapter 2 - Section 4 Minimizing Bias in Psychological Research Flashcards
What is bias?
Nonrandom (directed) effects caused by some factor or factors extraneous to the research hypothesis.
What is the difference between random variation in behavior and bias?
It is like the difference between the sets of target holes produced by a novice archer and by a skilled archer whose bow sights are misaligned.
Why is bias a more serious problem in research than random variation in behavior?
Bias is a very serious problem in research because statistical techniques cannot identify it or correct for it.
Whereas error only reduces the chance that researchers will find statistically significant results (by increasing the variability of the data), bias can lead researchers to the false conclusion that their hypothesis has been supported when, in fact, some factor irrelevant to the hypothesis has caused the observed results.
What are types of bias?
1 Sampling biases
2 Measurement biases
3 Expectancy biases (p. 46)
When is a group a biased sample?
If the members of a particular group are initially different from those of another group in some systematic way, or are different from the larger population that the researcher is interested in.
Conducting research with a biased sample is like shooting with a bow whose sights are misaligned. No matter how large the sample, the results will be off target.
A sample is biased when it is not representative of the larger population that the researchers are trying to describe. (p. 46)
What makes a measure good?
It should be both reliable and valid. (p. 47)
What is reliability?
A measure is reliable to the degree that it yields similar results each time it is used with a particular subject under a particular set of conditions, sometimes referred to as replicability.
A psychological test is not reliable if the scores are greatly affected, in a random manner, by the momentary whims of the research subjects.
Because it is a source of error, low reliability decreases the chance of finding statistical significance in a research study. (p. 47)
What is a second type of reliability and what is its requirement?
Interobserver reliability: the same behavior seen by one observer is also seen by a second observer.
This requires that the behavior in question be carefully defined ahead of time. This is done by generating an operational definition, specifying exactly what constitutes an example of your dependent measure. (p. 47)
What is validity?
It is an even more critical issue than reliability because lack of validity can be a source of bias.
A measurement procedure is valid if it measures or predicts what it is intended to measure or predict.
A procedure may be reliable and yet not be valid. For example, assessing intelligence in adults by measuring thumb length is highly reliable (you would get nearly the same score for a given person each time) but almost certainly not valid (thumb length is almost assuredly unrelated to adult intelligence).
This invalid measure exemplifies bias because it would produce false conclusions, such as the conclusion that tall people (who would have longer thumbs) are more intelligent than short people. (p. 48)
What is face validity?
If common sense tells us that a measurement procedure assesses the intended characteristic, we say the procedure has face validity.
A test of ability to solve logical problems has face validity as a measure of intelligence, but thumb length does not. (p. 48)
How can we assess the validity of a measurement procedure?
By correlating the scores of a measurement procedure with another, more direct index of the characteristic that we wish to measure or predict.
In that case, the more direct index is called the criterion, and the validity is called criterion validity. (p. 48)
What are observer-expectancy biases?
Being human, researchers inevitably have wishes and expectations that can affect how they behave and what they observe when recording data. A researcher who desires or expects a subject to respond in a particular way may unintentionally communicate that expectation and thereby influence the subject’s behavior. (p. 49) In addition to influencing subject’s behavior, observers’ expectations can influence observers’ perceptions or judgments concerning that behavior. (p. 51)
How can the supposed phenomenon of facilitated communication by people with autism be explained as an observer-expectancy effect?
The original observers of facilitated communication, who were also the original facilitators, were deluded by a powerful effect of their own expectations. To understand that effect, imagine that you are a facilitator who truly believes that the person with autism you are helping can type meaningful messages. At any given time during the facilitation, you have some idea in mind (perhaps unconsciously) of what the person is trying to type and what letter should come next. Your expectation that a particular letter will be typed next leads you to feel that the person’s finger is moving toward that letter on the keyboard, so you experience yourself as merely “facilitating” that movement, when you are actually guiding it and creating it. (p. 50)
What is autism?
A disorder characterized by a deficit in the ability to form emotional bonds and to communicate with other people; it typically manifests before age 3. Some people with autism are almost completely unable to use either spoken or written language. (p. 49)
What is the best way to prevent observer-expectancy effects?
To keep the observer blind - that is, uninformed - about those aspects of the study’s design that could lead him or her to form potentially biasing expectations.
Thus, in a between-groups experiment, a blind observer would not be told which subjects received which treatment.
