Research Ethics and Evaluating Quantitative Research Paper
Experimental and Non-experimental Research Design
Nursing research is extensive, and researchers use different designs to collect data and make inferences about various phenomena. Some researchers prefer the experimental design, while others rely on the non-experimental design. The main difference between these designs is how they deal with variables. Experimental design allows manipulation of variables, but the non-experimental design does not (Harding et al., 2021). Practical examples can help elucidate the differences between experimental and non-experimental research designs.
A suitable example of experimental research design is testing a new depression medication through a randomized controlled trial. In this experiment, the experimental group receives the medication while the control group receives a placebo. Participants can only belong to one of the groups. Non-experimental research may be carried out on the treatment to determine its characteristics, such as the quantity and chemical components. Another appropriate example is an experiment on the effectiveness of physical exercise on diabetic adults. One group goes through intensive exercise without a change in diet while the other participates in dietary modifications. Non-experimental research can be assessing the features of dietary modifications necessary to reducing obesity.
Regarding the levels of control, experimental research design exerts control on extraneous variables. Laksana et al. (2020) described extraneous variables as the variables not being investigated but can affect the outcomes of the research study. As a result, experimental research tampers with the natural setting. On the other hand, experimental research environments are natural and do not control extraneous variables. Harding et al. (2021) further posited that the most distinct difference between experimental and non-experimental research design is the researcher’s ability to control independent variables. Experimental research is manipulative, while non-experimental research does not interfere with the natural setting. The control is justified since researchers should control variables that can lead to inaccurate deductions.
Harding, D. J., Sanbonmatsu, L., Duncan, G. J., Gennetian, L. A., Katz, L. F., Kessler, R. C., … & Ludwig, J. (2021). Evaluating contradictory experimental and nonexperimental estimates of neighborhood effects on economic outcomes for adults. Housing Policy Debate, 1-34. https://doi.org/10.1080/10511482.2021.1881985
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Laksana, E., Aczon, M., Ho, L., Carlin, C., Ledbetter, D., & Wetzel, R. (2020). The impact of extraneous features on the performance of recurrent neural network models in clinical tasks. Journal of Biomedical Informatics, 102, 103351. https://doi.org/10.1016/j.jbi.2019.103351
Discussion 2: Sampling Theory and Generalizability
Like in other types of research, it is challenging to conduct a study involving the entire population in nursing. As a result, researchers use a sample to represent the general population. The sample should have similar features to the studied population. Sampling theory and generalizability are common terms in research where sampling is involved.
Sampling theory is a branch of statistics used in nursing research to determine the link between the population group and the randomly selected sample. According to Peregrine (2018), sampling theory is the study of the relationship between the general population and the sample representing the population in research. A suitable example is where a researcher exploring work satisfaction among nurses in a country would first randomly select cities followed by a random selection of hospitals. Next, the researcher randomly selects nurses to represent the entire population, convinced that there is no significant statistical difference between the characteristics of the sample and the general population of nurses. From this example, it is right to deduce that sampling theory’s primary purpose is statistical inference. It helps researchers to generalize the particulars of a sample to represent a broader population.
It is impractical to conduct an experiment that involves the entire population. Accordingly, the basic concept of generalizability is straightforward. As Malmivaara (2019) explained, generalizability involves drawing broad inferences from particular observations from a population sample. It usually applies to quantitative research. In clinical settings, research results are considered generalizable when used to inform clinical decisions to the entire population. For accurate generalization, researchers should use appropriate sample sizes and sampling techniques. It is also important to use appropriate statistical applications to make correct inferences.
Malmivaara, A. (2019). Generalizability of findings from randomized controlled trials is limited in the leading general medical journals. Journal of clinical epidemiology, 107, 36-41. https://doi.org/10.1016/j.jclinepi.2018.11.014
Peregrine, P. (2018). Sampling theory. The Encyclopedia of Archaeological Sciences, 1-3. https://www.researchgate.net/profile/Peter-Peregrine/publication/247987195_Sampling_in_archaeology/links/5d9606a3299bf1c363f5708b/Sampling-in-archaeology.pdf
Topic 3 Discussion 1
Provide examples of experimental and nonexperimental research design. Contrast the levels of control applied to each.
Topic 3 Discussion 2
Describe sampling theory and provide examples to illustrate your definition. Discuss generalizability as it applies to nursing research
PLEASE ENSURE THAT CONTENT IS ORIGINAL AND HAS NOT BEEN USED BEFORE. EACH DISCUSSION SHOULD BE 1 PAGE.
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