7 5: Between Subject Designs
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Using this design, participants in the various conditions are matched on the dependent variable or on some extraneous variable(s) prior the manipulation of the independent variable. This guarantees that these variables will not be confounded across the experimental conditions. For instance, if we want to determine whether expressive writing affects people’s health then we could start by measuring various health-related variables in our prospective research participants. We could then use that information to rank-order participants according to how healthy or unhealthy they are. Next, the two healthiest participants would be randomly assigned to complete different conditions (one would be randomly assigned to the traumatic experiences writing condition and the other to the neutral writing condition).
Individual differences may threaten validity
The next two healthiest participants would then be randomly assigned to complete different conditions, and so on until the two least healthy participants. This method would ensure that participants in the traumatic experiences writing condition are matched to participants in the neutral writing condition with respect to health at the beginning of the study. If at the end of the experiment, a difference in health was detected across the two conditions, then we would know that it is due to the writing manipulation and not to pre-existing differences in health.
IV. Chapter 4: Psychological Measurement
The pretest posttest design handles several threats to internal validity, such as maturation, testing, and regression, since these threats can be expected to influence both treatment and control groups in a similar (random) manner. For instance, mortality can be a problem if there are differential dropout rates between the two groups, and the pretest measurement may bias the posttest measurement (especially if the pretest introduces unusual topics or content). As seen above, sometimes your independent variables will dictate the experimental design.
Extraneous variables (EV)
Fig. 1. Inter-Group Helping Relations as affected by perceived... - ResearchGate
Fig. 1. Inter-Group Helping Relations as affected by perceived....
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In a mixed factorial design, one variable is altered between subjects and another is altered within subjects. A between-subjects study design aims to enable researchers to determine if one treatment condition is superior to another. Researchers will manipulate an independent variable to create at least two treatment conditions and then compare the measures of the dependent variable between groups. Each level of one independent variable is combined with each level of every other independent variable to create different conditions. To detect a statistically significant difference between two conditions, you’ll often need a fairly large number of a data points (often above 40) in each condition. If you have a within-subject design, each participant will provide a data point for each level of the independent variable.
Between-subjects designs also prevent fatigue effects, which occur when participants become tired or bored of multiple treatments in a row in within-subjects designs. 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. There would be no experimental or control groups because all participants undergo the same procedures.
Matched Groups
Each group of children is given a different educational program, along with a control group sticking with the original. All of the groups are tested, at the end, to determine which program delivered the most improvement. In both differences between groups and differences within groups, we will generally look at differences between means on some variable of interest. When we talk about a Mean Difference, we are talking about the difference between the mean of one group and the mean of another group in the case of differences between groups. In the case of differences within groups, we look at differences in means between two or more different points in time when measurements are taken.
A large participant pool is necessary
Researchers test the same participants repeatedly to assess differences between conditions. A between-subjects design is also called an independent measures or independent-groups design because researchers compare unrelated measurements taken from separate groups. Once the study is designed, we need to obtain a sample of individuals to include in our experiment. Participants are the subjects of psychological research, and as the name implies, individuals who are involved in psychological research actively participate in the process. Often, psychological research projects rely on college students to serve as participants.
The between-group design is widely used in psychological, economic, and sociological experiments, as well as in several other fields in the natural or social sciences. Having performed analyses inconsistent with the study design, and that introduce rather than control these threats, the authors reach conclusions that are difficult to justify. A between subjects design is a way of avoiding the carryover effects that can plague within subjects designs, and they are one of the most common experiment types in some scientific disciplines, especially psychology. Finally, when the number of conditions is large experiments can use random counterbalancing in which the order of the conditions is randomly determined for each participant. Using this technique every possible order of conditions is determined and then one of these orders is randomly selected for each participant.
For this reason, there is also the risk of order effects—participants performing differently in each condition because of the order they were presented. A participant who tests a single car-rental site will have a shorter session than one who tests two. Shorter sessions are less tiring (or boring) for users and can also be more appropriate for remote unmoderated testing (especially since tools like UserZoom usually require a fairly short session length). Condition one attempted to recall a list of words that were organized into meaningful categories; condition two attempted to recall the same words, randomly grouped on the page. To assess the difference in reading comprehension between 7 and 9-year-olds, a researcher recruited each group from a local primary school.
Thus, the inquiry is broadened and extended beyond the effect of one variable (as with within-subject design). Additionally, this design saves a great deal of time, which is ideal if the results aid in a time-sensitive issue, such as healthcare. 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. This type of design is often called an independent measures design because every participant is only subjected to a single treatment.
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