What is a disadvantage of a between-subjects design?
The main disadvantage with between subjects designs is that they can be complex and often require a large number of participants to generate any useful and analyzable data. Because each participant is only measured once, researchers need to add a new group for every treatment and manipulation.
Are surveys between or within-subjects design?
In a between-subjects design, each person who takes the survey sees one ad OR the other—but not both. In this design, your sample would be split into two groups of respondents, one group that sees the clothing store ad and one that sees the ad with the shopping bags.
When would you use a between-subjects design?
A between-subjects design is also useful when you want to compare groups that differ on a key characteristic. This characteristic would be your independent variable, with varying levels of the characteristic differentiating the groups from each other.
What is an advantage of the between-subjects design versus the within-subjects design?
Perhaps the most important advantage of within-subject designs is that they make it less likely that a real difference that exists between your conditions will stay undetected or be covered by random noise. Individual participants bring in to the test their own history, background knowledge, and context.
What confound would you worry about if you have a between subject design?
Is to randomly assign participants to conditions and assume the groups are not dramatically different in terms of their subject variables. that between- subject designs are always vulnerable to confounding subject variables( random assignment is not guaranteed to work).
Under what circumstances is a within subjects design not a good choice for a research study?
A within-subjects design should be avoided in studying effects of several treat- ments when the researcher is interested in the effects of the treatments in the absence of practice and practice is likely to affect per- formance (either a main effect of successive tests or an interaction of successive tests with …
What is an example of within subject design?
Another common example of a within-subjects design is medical testing, where researchers try to establish whether a drug is effective or whether a placebo effect is in order. The researchers, in the crudest form of the test, will give all of the participants the placebo, for a time, and monitor the results.
What is an example of a between-subjects design?
For example, in a between-subjects design investigating the efficacy of three different drugs for treating depression, one group of depressed individuals would receive one of the drugs, a different group would receive another one of the drugs, and yet another group would receive the remaining drug.
What is a major advantage of a within-subjects design quizlet?
What is a major advantage of a within-subjects design? It helps us detect the impact of the independent variable.
When using a within-subjects design you need counterbalance to account for?
Counterbalancing is a procedure that allows a researcher to control the effects of nuisance variables in designs where the same participants are repeatedly subjected to conditions, treatments, or stimuli (e.g., within-subjects or repeated-measures designs).
Why is a longitudinal design considered a within-subjects design quizlet?
Why is a repeated-measures design considered a within-subjects design? – Participants are measured on the dependent variable after exposure to each level of the independent variable. – Participants are measured twice, once at the beginning of the study and once at the end of the study.
Why is a repeated measure design considered a within-subjects design?
A within-subjects design is also called a dependent groups or repeated measures design because researchers compare related measures from the same participants between different conditions. All longitudinal studies use within-subjects designs to assess changes within the same individuals over time.
Is longitudinal a within-subjects design?
Longitudinal designs are typically within-subjects or repeated measurement designs. ! HOWEVER, they can also be between-subjects or independent groups designs. This would be the case if in studying a given cohort at each individual time of measurement, we selected a different sample from that same cohort.
Why is a pretest-posttest design considered a within-subjects design?
The pretest-posttest design is much like a within-subjects experiment in which each participant is tested first under the control condition and then under the treatment condition.
Can pretest and posttest be the same?
Answer: Students scores are lower on the pre-test because they have not yet studied the material which is tested. Scores are expected to be higher on the post-test because the students have already studied the tested material. Remember that the pre-test and post-test are the same.
What can be gained from examining pretest and posttest data?
By including the Pretest data in the analysis, a researcher can increase the probability of detecting a significant difference between groups, thereby increasing the power of the statistical test. One of the most commonly used methods in analyzing Pretest-Posttest data is the difference method, or gain in scores.
What characteristic differentiates a pretest-posttest design from a time series design?
What characteristic differentiates a pretest-posttest design from a time-series design? A simple modification of the pretest-posttest design minimizes the threats to internal validity and produces a much stronger research design.
What are the three requirements for a between subjects design to be an experimental research design?
Terms in this set (70)
- levels of a between-subjects factor are manipulated with a control group present.
- participants are assigned randomly to each group or level of the between-subjects factor (allows for holding other variables constant — i.e., controls for the influence of other variables)
Which of the following is a possible disadvantage of pretest-posttest research designs?
The only disadvantage of the pretest-posttest control group design compared to the posttest only design, is that there can be a threat to internal validity called the testing threat. As was discussed in an earlier chapter, this threat can occur when there is an interaction between the pretest and the treatment.
What is the difference between time series design and interrupted time series design?
The time series refers to the data over the period, while the interruption is the intervention, which is a controlled external influence or set of influences. Effects of the intervention are evaluated by changes in the level and slope of the time series and statistical significance of the intervention parameters.
When would you use an interrupted time-series design?
Interrupted time series can be used when: we have data about an outcome over time (longitudinal data) AND. we want to understand how and if the outcome has changed after an intervention, a policy, or a program that was implemented for the full population at one specific point in time.
What is the difference between a time series design and an interrupted time-series design quizlet?
What is one difference between a time-series design and an interrupted time-series design? Time series examines the effect of a treatment and interrupted time series examines the effect of an outside event.
What makes a study externally valid?
External validity is the extent to which you can generalize the findings of a study to other situations, people, settings and measures. In other words, can you apply the findings of your study to a broader context? The aim of scientific research is to produce generalizable knowledge about the real world.
How do you know if a study is valid?
8 ways to determine the credibility of research reports
- Why was the study undertaken? …
- Who conducted the study? …
- Who funded the research? …
- How was the data collected? …
- Is the sample size and response rate sufficient? …
- Does the research make use of secondary data? …
- Does the research measure what it claims to measure?
Can a test be reliable without being valid?
Although a test can be reliable without being valid, it cannot be valid without being reliable. If a test is inconsistent in its measurements, we cannot say it is measuring what it is intended to measure and, therefore, it is considered invalid.