PSY 5107 Assignment Discriminate Quasi-Experimental Research
PSY 5107 Assignment Discriminate Quasi-Experimental Research
There are a few key differences between quasi-experiments and true experiments. The most significant difference is that quasi-experiments do not involve the random assignment of participants to conditions. This means that there is always some degree of selection bias in quasi-experiments, as the participants who choose to be in a study may be different from those who do not (Rinella et al., 2020). Additionally, it is more difficult to rule out alternate explanations for results in quasi-experiments than it is in true experiments. Finally, quasi-experiments typically have smaller sample sizes than true experiments, which can lead to less reliable results. The purpose of this assignment is to differentiate between true experimental and quasi-experimental designs with an example.
A quasi-experimental research design is a type of research design that does not involve randomly assigning participants to experimental and control groups. Rather, quasi-experimental designs allow for the study of differences among individuals within pre-existing groups (e.g., people who already have different levels of exposure to a risk factor) (Pabel, 2021). Quasi-experimental research design is often used when it would be unethical or impossible to randomly assign participants to groups (e.g., testing a new cancer drug on people who have not yet been diagnosed with cancer).
Hypothetical Example of a Quasi-Experimental Research Design
A research was conducted to determine the effects of poverty on intelligence among the urban population in New York. The research mainly involved comparing the intelligent quotient (IQs) of adults who grew up in poverty with the IQs of adults who grew up in wealthy families. The main objective of the study was to test whether poverty has significant impacts on the intelligence or IQ.
Study’s hypothesis (Ho): poverty has no significant impacts on the intelligence among the
Alternative hypothesis (H1): poverty has significant impacts on the intelligence among the
The Issue of Random Assignment
A quasi-experimental research design is a type of research design that does not involve randomly assigning participants to experimental and control groups. Rather, quasi-experimental designs allow for the study of differences among individuals within pre-existing groups (e.g., people who already have different levels of exposure to a risk factor). From the hypothetical study design, researchers want to compare the IQs of adults who grew up in poverty with the IQs of adults who grew up in wealthy families. By doing so, they can study the effects of poverty on intelligence without randomly assigning people to poverty and wealth conditions (Viglia & Dolnicar, 2020). From the study, the issue of random assignment is social economic status (poverty/wealth). In other words, the researchers want to determine the impact of poverty/wealth on intelligence.
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From the study design, it would be necessary to conduct a quasi-experimental study and not a true experiment because there are already pre-existing groups (poor and wealthy). In other words, researchers in this case do not need to randomly assign participants into two groups. Instead, they only need to take into account the differences that exist between the groups that have been considered before embarking on the research process. In a true experimental study, researchers would randomly assign participants to two groups—an experimental group and a control group (Ogilvie et al., 2020). They would then give the experimental group the treatment and compare their results to those of the control group; this, however, is not possible in this case.
How the Group Membership Could Be Impactful In Understanding the Results
The group membership in this quasi-experimental research could be impactful in understanding the results. That is because, when the groups are not randomly assigned, but are instead chosen by the researcher as in this case, there is a potential for bias to enter into the study (Siedlecki, 2020). For example, if one group (the wealthy or the poor) is significantly larger than another, or if one group is more highly motivated than another, then it could very well be that the results of the study are due to these factors and not to the intervention itself.
Converting Quasi-Experimental Study into a True Experimental Study
To convert the hypothetical quasi-experimental study provided into a true experimental study, researchers would need to randomly assign participants to one of two groups – an intervention group and a control group (poor or wealthy). Then, they would need to measures the outcomes of interest for both groups. Finally, they would need to analyze the data and compare the two groups.
The term “quasi-experimental design” is used to refer to any study that does not meet the requirements of a true experimental design. In other words, quasi-experimental studies are observational studies, rather than experiments (Siedlecki, 2020). There are a number of reasons why researchers might opt for a quasi-experimental design over a true experimental design. Quasi-experiments may be used when it is not possible to randomly assign participants to different groups (i.e., when there is no way to control who receives the treatment and who does not). Quasi-experiments may also be used when it is unethical or impractical to randomly assign participants to different groups (for example, in studies involving human subjects).
Ogilvie, D., Adams, J., Bauman, A., Gregg, E. W., Panter, J., Siegel, K. R., … & White, M. (2020). Using natural experimental studies to guide public health action: turning the evidence-based medicine paradigm on its head. J Epidemiol Community Health, 74(2), 203-208. http://dx.doi.org/10.1136/jech-2019-213085
Pabel, A. (2021). An 4 Application of Quasi-Experiments to Study Humour in Tourism Settings Guided by Post-Positivism. Research Paradigm Considerations for Emerging Scholars, 38. https://doi.org/10.21832/9781845418281
Rinella, M. J., Strong, D. J., & Vermeire, L. T. (2020). Omitted variable bias in studies of plant interactions. Ecology, 101(6), e03020. https://doi.org/10.1002/ecy.3020
Siedlecki, S. L. (2020). Quasi-experimental research designs. Clinical Nurse Specialist, 34(5), 198-202. 10.1097/NUR.0000000000000540
Viglia, G., & Dolnicar, S. (2020). A review of experiments in tourism and hospitality. Annals of Tourism Research, 80, 102858. https://doi.org/10.1016/j.annals.2020.102858