Researchers must make informed choices about the type of statistical analysis that best addresses the research question. For the past several weeks, you have been considering how and when a particular statistic should be employed. This week, you have focused on the use of nonparametric tests.
Nonparametric methods are useful to researchers in performing statistical analyses of quantitative data sets that do not follow normal distributions and that have inconsistent variation. Nonparametric methods are often applied when ordinal-level data are collected and, as such, rely on fewer assumptions than their parametric counterparts.
In this Discussion, you examine the two articles in this week’s Learning Resources, both of which employ nonparametric methods of statistical analysis. In addition, as the final week of exploring quantitative statistics, you consider which statistical method is most frequently used in your area of nursing practice.
- 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?
By tomorrow Thursday 10/19/17 by 5pm, write a minimum of 550 words in APA format with at least 3 references from the list of Required Readings below. Include the level one headings as numbered (1, 2 &3) below.
Post a cohesive response that addresses the following:
1) Critically analyze each article, including the items noted above. (See attached file for 1 article & follow this link for the 2nd article: http://www.ajmc.com/journals/issue/2010/2010-07-vol16-n07/AJMC_2010jul_Tija_489to496).
2) 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.
3) Based on your area of nursing practice (Critical Care), 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.
Gray, J.R., Grove, S.K., & Sutherland, S. (2017). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (8th ed.). St. Louis, MO: Saunders Elsevier.
Chapter 25, “Using Statistics to Determine Differences”
Statistics and Data Analysis for Nursing Research
Chapter 8, “Chi-Square and Nonparametric Tests”
This chapter defines nonparametric tests and chi-square tests of independence. Nonparametric tests measure nominal or ordinal variables, whereas chi-square tests are used to draw conclusions about population differences.
Fisher, K., Orkin, F., & Frazer, C. (2010). Utilizing conjoint analysis to explicate health care decision making by emergency department nurses: A feasibility study. Applied Nursing Research, 23(1), 30–35. doi: 10.1016/j.apnr.2008.03.004 (SEE ATTACHED FILE)
This article describes a study that employed conjoint analysis, a measurement technique incorporating simulation into experimental design to generate a mathematical model of individual decision making. The study focused on nurses’ decisions related to the care of patients with intellectual disability and used contingency tables and nonparametric tests to analyze the data.
Tjia, J., Field, T., Garber, L., Donovan, J., Kanaan, A., Raebel, M., … Gurwitz, J. (2010). Development and pilot testing of guidelines to monitor high-risk medications in the ambulatory setting. American Journal of Managed Care, 16(7), 489–496. (Follow this link: http://www.ajmc.com/journals/issue/2010/2010-07-vol16-n07/AJMC_2010jul_Tija_489to496)
Development and pilot testing of guidelines to monitor high-risk medications in the ambulatory setting. American Journal of Managed Care, 16(7) by Tjia, J., Field, T., Garber, L., Donovan, J., Kanaan, A., Raebel, M., & Gurwitz, J. Copyright 2010 by INTELLISPHERE, LLC. Reprinted by permission of INTELLISPHERE, LLC via the Copyright Clearance Center.
This article discusses a pilot test that aimed to catalog safety intervention trials by monitoring high-risk medications for efficacy, safety, and drug interactions. The statistical analysis of the study’s data included the use of nonparametric tests to examine trends across ordered groups of drugs.
Walden University. (n.d.). Nonparametrics. Retrieved August 1, 2011, from http://streaming.waldenu.edu/hdp/researchtutorials/educ8106_player/educ8106_nonparametric_tests.html