Experimental Questions
In what ways are (two levels) independent groups designs and (two levels) matched groups designs (a) similar or the same, and (b) distinct or different from each other?
Similar
Both the two-level independent group’s design and two matched group design focus on assessing a given treatment based on a control group. The exposure is random in both cases and follows a specific limit to help determine better outcomes based on the processes that have been incorporated within the analysis.
Difference
Two levels of independent groups design is a simple design which involves one group of individuals who are exposed to one level of a dichotomous variable. In contrast, a different group of people is exposed to the other level of the variable. There is a difference in the scores of the dependent variables between the two groups.
In a two matched group designs, subjects that have similar scores are grouped, and then they are randomly assigned one member of each pair to the experimental condition while the other member is placed in the control condition. Matched group designs do not focus on randomization but rather emphasize on matched groups approach (Patten & Newhart, 2017).
What are the three special-purpose control group designs and briefly describe each?
A control group is a vital part in research designs which allow researchers to minimize the effect of all the variable except the independent variable. The control group in research receives no intervention and form the basis to compared groups and determine the effect of the intervention. The three special-purpose control group designs include concurrent placebo control, no concurrent treatment control and historical controls (Bryman, 2016).
Placebo concurrent control is aimed at showing the difference between a given treatment and control group that is not exposed to the treatment. There is no focus on the existing sensitivity of the drug.
No treatment concurrent control is normally a randomized design. It does not have a specific approach to the selection of participants into the groups. Validation to detect the efficacy of the drug test is required.
The historical controls do not involve any form of randomization. Patients that are included in the control group were treated at an earlier time or in a different setting.
When portraying the means of the dependent variable in a study graphically, what are the guidelines that help determine whether to use a bar graph or a line graph?
It is essential to determine when to use line or bar graphs within a given context. When focusing on means, it is crucial to decide on how the information is utilized. Line graphs can be used when the ways that are calculated focus on data based on a longer period of time to help in showing the trend. Bar graphs can be utilized when the means are comparable within a given dataset. The type of data that is utilized should also help in presenting a clear emphasis on essential measures that help define the differences that exist in a particular dataset (Coolican, 2017).
In the research example that examined the effects of social skills training in children with autism, what was the matching variable, and why was it chosen?
The effects of social skills training in children are the matching variable that has been utilized in this research. This variable has been chosen, considering that it provides a different emphasis on the wellbeing of children autism.
What are the proper statistical analyses for the four designs that feature single factor multilevel designs?
The four designs include independent group design, matched group design, ex post facto design and repeated measures design.
The independent group design includes independent sample t-test.
Matched group design can be analyzed using a one-way analysis of variance.
Ex post facto design can be analyzed using multivariate analysis of variance.
Repeated measures design can be analyzed using repeated-measures analysis of variance.
What is the importance of the study about the Yerkes-Dodson Law that illustrates essential reasons for conducting studies using single factor multilevel experimental designs?
Yerkes-Dodson law identifies that performance is good at moderate levels of arousal and poor at both high and low levels of arousal. Single-factor multilevel experiment designs provide a stronger emphasis on the influence of each of the independent variable that is investigated within a given research context. Investigating the influence of each factor present a greater focus on better systems that help show a greater emphasis on important aspects that help build change when investigating a given intervention (Patten & Newhart, 2017).
When is a post hoc analysis in a one-way ANOVA conducted, and why is it computed?
A post hoc in one-way analysis of variance when the factor variable being investigated has three or more groups. This is aimed at determining whether there is a significant difference between the groups. A post hoc analysis can only be conducted when the one-way analysis of variance is significant.
Briefly describe the two-level ex post facto group design and the two-level repeated measure group design.
The Ex post facto design is a quasi-experimental study that aims at determining how an independent variable that is present in the study participants before the commencement of the study affect a dependent variable. The participants are not assigned randomly. Groups are composed of different distinct types of variables, such as male and female (Coolican, 2017).
Two-level repeated measure group design – within-subject design. Within-subject design is an experimental design where all participant are exposed to every treatment that is being investigated.
Ex post facto design – between-subject design- it is a study design where different people test each of the treatment intervention investigated. Each individual is only exposed to a single user interface.
References
Bryman, A. (2016). Social research methods. Oxford university press.
Coolican, H. (2017). Research methods and statistics in psychology. Psychology Press.
Patten, M. L., & Newhart, M. (2017). Understanding research methods: An overview of the essentials. Taylor & Francis.
Walliman, N. (2017). Research methods: The basics. Routledge.