In a matched-groups design studying the effect of expressive writing on health, researchers rank participants by health and then randomly assign the two least healthy participants to different conditions. What does this method ensure?
Explanation
A matched-groups design is a powerful technique in between-subjects research to control for a specific, important extraneous variable. By matching participants (e.g., on health) and then randomly assigning them, researchers can be more confident that the groups are equivalent on that variable before the manipulation begins.
Other questions
In a between-subjects experiment, how is each participant tested?
What is the primary method researchers use to control for extraneous participant variables in a between-subjects experiment, ensuring groups are highly similar on average?
What is the defining feature of a within-subjects experiment?
What is the primary advantage of a within-subjects experiment over a between-subjects experiment?
Which type of effect occurs when participants perform a task better in later conditions of a within-subjects experiment simply because they have had a chance to practice it?
What is the primary purpose of counterbalancing in a within-subjects experiment?
In a study with three conditions (A, B, and C), how many different orders are possible for complete counterbalancing?
How many different orders would be required for complete counterbalancing in an experiment with five conditions?
An effect of being tested in one condition on a participant's behavior in a later condition is known as a:
In a between-subjects experiment, what is the purpose of a matched-groups design?
According to the chapter, when is a between-subjects design a better choice than a within-subjects design?
Which technique involves arranging conditions in a random sequence where all conditions occur once before any are repeated, with the conditions in each 'block' being in a random order?
What type of carryover effect is illustrated when judging an average-looking defendant more harshly after just having judged a very attractive defendant?
What is a primary distinction between random sampling and random assignment?
A more efficient way of counterbalancing than complete counterbalancing, especially with a larger number of conditions, is a:
According to the chapter, a study that does not involve random assignment in some form is not considered what?
In Michael Birnbaum's study where participants rated the size of numbers, why did participants in the between-subjects design rate the number 9 as larger than the number 221?
Which of the following scenarios is an example of a simultaneous within-subjects design?
What is the primary reason that random assignment is not guaranteed to control all extraneous variables?
A fatigue effect is a type of carryover effect where participants' performance in later conditions:
If a researcher wants to study the effectiveness of a new psychotherapy that produces long-term changes, which experimental design would be most appropriate?
How many conditions must an experiment with four versions using a Latin square design have?
A researcher with a sample of 60 people with agoraphobia assigns 20 to Treatment A, 20 to Treatment B, and 20 to a control group. What type of experimental design is this?
In a matched-groups design to study a new health intervention, how would a researcher handle the two healthiest participants in the sample?
What is one reason that random assignment works better than one might expect, according to the text?
If a within-subjects design is difficult or impossible to carry out, what does the chapter suggest a researcher should do?
Which of the following meets the two criteria for the strictest sense of random assignment?
One problem with strict random assignment procedures like coin flipping is that they are likely to result in what?
When participants in a within-subjects design guess the research hypothesis because of the sequence of conditions, this can lead them to...
What does a Latin square design for an experiment with 6 conditions look like in terms of dimensions?
When is random counterbalancing a potential option for researchers?
Which of these is NOT listed as a type of carryover effect in the chapter?
In a between-subjects experiment, what is the ideal state for the different participant groups at the start of the study?
What is one way to think about what counterbalancing accomplishes regarding the order of conditions?
If a researcher wants to study how remembering negative adjectives compares to remembering positive ones, and has participants study a single list with both types of words, what design is being used?
Why is a between-subjects design considered conceptually simpler than a within-subjects design?
If a study has four conditions, how many different orders would be required for complete counterbalancing?
What is the primary disadvantage of within-subjects designs?
What is the relationship between a within-subjects design and 'noisy' data?
In a Latin square design, if you have four treatments (A, B, C, D), a valid first row for the square could be 'A B C D'. What would be a valid second row according to the example in the text?
According to the chapter, a researcher should never throw away data they have already collected in a between-subjects study for what reason?
What is an 'order effect' in the context of a within-subjects experiment?
Why might a researcher choose a within-subjects design if they have a limited number of available participants?
If a confound is likely to be detected when an experiment is replicated, what does this suggest about the initial random assignment?
The primary distinction between a between-subjects and a within-subjects experiment is based on what?
How many orders would a Latin Square design for an experiment with 6 conditions require, compared to the 720 orders for complete counterbalancing?
If a researcher wants to test participants in a doctor's waiting room and has limited time with each person, which design would be the better choice?
Random assignment plays an important role in both between-subjects and within-subjects designs. How does its application differ between the two?
What is the upshot or main takeaway regarding random assignment to conditions, despite its fallibility?