Parametric Nonparametric Statistical Tests Healthcare Resear Chapter

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RESPONSE R (TWO)

Response R (Two)


K. Kim


In the first post, K. Kim opted to focus on a descriptive analysis to gather socio-demographic data and medical history of the sample to assess the prevalence of lifetime and current prescription-opioid use disorders and opioid misuse. According to Macfarlane et al. (2020) opioids are routinely used in the treatment of cancer patients. However, misuse of the said opioids has been rather rampant (Macfarlane et al., 2020). Apart from the descriptive analysis highlighted by my colleague, the person-level sample weight can be used to analyze data (Hudgins et al, 2019). In this method, the weights of the sample are adjusted by use of generalized exponential model. The said model adjusts in case of extreme weights, post-stratification, and survey non-response so as to yield characteristics and occurrences that are unbiased (Hudgins et al, 2019). STATA Version 15 is used to analyze the data. The strength of the study is that the response rate of the analyzed years was high. However, the study did not include people in prison, military personnel, and homeless people. In addition, patterns of opioid use were…

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…that do not require normal distribution assumption while parametric tests require equal variance and normality.

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However, the said tests were not used in the article by Woo et al (2017). In essence, nonparametric tests, as Orcan (2020) points out, are not founded upon assumptions. The author further indicates that in those instances whereby data follows a specific distribution, parametric tests (such as t-test and ANOVA) come in handy. One strength of the study has got to do with the methodology deployed. This would largely have a positive impact on evidence-based practice.….....

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