Assignment: Statistical Analyses in Nursing Essay
Assignment: Statistical Analyses in Nursing Essay
Clinical decision is of utmost importance in the provision of quality health outcomes. Contingent upon this premise, the two articles establish decision-making procedures and practice guidelines relevant for clinical practice. The first study assesses the feasibility of decision-making processes by nurses stationed at the emergency department of a care facility (Fisher, Orkin & Frazer, 2010). On the other hand, the work of Tjia et al. (2010) purposes to develop guidelines required to monitor the dispensation of high-risk medications while at the same time establish the prevalence of existing laboratory testing concerning these medications. In order to draw clinical evidence on a factor in decision making, the article by Fisher, Orkin and Frazer (2010) employed the usage of nonparametric tests comprising Fisher’s exact tests and chi-square. The study relied on conjoint analysis to reflect upon the decision-making patterns. The results of this study provided quality outcomes by demonstrating that nurses depended on the functional status of patients, future health status, and family input to undertake decisions on healthcare delivery for their clients. The article by Tjia et al. (2010) utilized t-test and Likert-type scale to formulate guidelines for the utilization of high-risk drugs and to monitor the frequency of dispensing them. The non-parametric test was instrumental in developing medication dispensing guidelines in terms of drug classes, the frequency of medication, monitoring and laboratory testing for efficacy.
According to numerous empirical studies, parametric parameters receive useful application in the testing of study group means. Nevertheless, the effectiveness of the methodology remains debatable within the context of the present articles. For instance, the use of t-test and ANOVA requires normal distribution of the applicable data regarding the research. Since data from the two articles were not distributed, it became paramount for the authors to consider skewing of non-normal distribution to produce the results (Gibbons & Chakraborti, 2011). Therefore, the approach remains embedded on assumptions and as such it has a high vulnerability to error. However, the assertion receives higher applicability in the second article. Nonetheless, the application of ANOVA and t-test requires studies that have a broad distribution of sample sizes, a threshold that neither of the two articles met.
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Despite providing results on the clinical decision and high-risk drug dispensing techniques, certain strengths and weakness characterized the studies. The first article used conjoint analysis techniques to design a workable mathematics model required for
clinical decision-making process for nurses in the emergency department (Fisher, Orkin & Frazer, 2010). However, the technique involving proxy decision-making for this study is complex considering the premise that it does not uniformly address the responses of all nurses. As such, the study could be subject to speculation hence casting doubt on the accuracy of information obtained from the first study. In the article by Tjia et al. (2010), the selected study design captured a multispecialty population and therefore provided a reflection of clinical practice in the United States of America. However, utilization of the Likert-type scale could subject the study outcomes to errors due to a lack of consensus on the questions administered to participants. Considerably, findings and recommendations in the work of Fisher, Orkin and Frazer (2010) provide the need for aligning clinical decisions as per the patients in the emergency department for purposes of improving the quality of care. Correspondingly, the other article offers guidelines for safe administration of high-risk medications to establish an evidence-based practice in a healthcare setting.
In the entire coursework, the present author discovers nonparametric tests as commonly applied to the processes of analyzing data. Specifically, chi-square dominates most of the literature review in clinical research. Evidently, the adoption of this test has demonstrated effectiveness in the analysis of nominal data. Furthermore, the technique has a high level of accuracy since it has received comparison with observed frequencies obtained from null hypotheses. Nevertheless, the adoption of other nonparametric tests such as the Wilcoxon matched-pairs test, Mann-Whitney U and Kruskal-Wallis tests does not readily occur since they measure rank-ordered data. According to Gibbons and Chakraborti (2011), the application of the above-mentioned non-parametric tests in multifarious clinical studies does not normally occur since outliers have the capacity to obscure the outcomes. Moreover, the outliers have minimal impact on the chi-square tests.
Review the articles presented in this week’s Learning Resources and analyze each study’s use of nonparametric tests.
Critically analyze each article, considering the following questions in your analysis:
What are the goals and purpose of the research study each article describes?
How are nonparametric tests used in each study? What are the results of their use?
Why are parametric methods (t tests and ANOVA) inappropriate for the statistical analysis of each study’s data?
What are the strengths and weaknesses of each study (e.g., study design, sampling, and measurement)?
How could the findings and recommendations of each study contribute to evidence-based practice in the health care field?
Reflect on the quantitative statistical analyses presented throughout this course in the research literature, the Learning Resources, media presentations, and those articles you reviewed for your abbreviated research proposal.
Ask yourself: Which method is most commonly used in research studies that pertain to my area of nursing practice, and why this might be so?
Post a cohesive response in your small group that addresses the following:
Critically analyze each article, including the items noted above.
Identify one statistical analysis method that you found recurring in many of the articles you used in your literature review for your research proposal. This method does not necessarily have to be nonparametric.
Based on your area of nursing practice, which method of statistical analysis is most frequently used in the research literature? Why do you think other forms of statistical analysis are less frequently used? Provide a rationale for your response.