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Logistic Regression in Nursing Practice

To prepare:

Review the three articles in this week's Learning Resources and evaluate their use of logistic regression. Select one article that interests you to examine more closely in this Discussion

Critically analyze the article you selected considering the following questions:

What are the goals and purposes of the research study the article describes?

How is logistic regression used in the study? What are the results of its use?

What other quantitative and statistical methods could be used to address the research issue discussed in the article?

What are the strengths and weaknesses of the study?

How could the weaknesses of the study be remedied?

How could findings from this study contribute to evidence-based practice, the nursing profession, or society?

Post 4 paragraph that addresses the following:

1.In the first line of your posting, identify the article you examined, providing its correct APA citation.

2. Post your critical analysis of the article as outlined above.

3.Propose potential remedies to address the weaknesses of each study.

4.Analyze the importance of this study to evidence-based practice, the nursing profession, or society.

Provide 3 references

1.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 24, "Using Statistics to Predict"

2. Statistics and Data Analysis for Nursing Research

Chapter 9, "Correlation and Simple Regression" (pp. 208-222)

3. Select One Article from below for your assignment discussion:

Hoerster, K. D., Mayer, J. A., Gabbard, S., Kronick, R. G., Roesch, S. C., Malcarne, V. L., & Zuniga, M. L. (2011). Impact of individual-, environmental-, and policy-level factors on health care utilization among US farmworkers. American Journal of Public Health, 101(4), 685-692.

Tritica-Majnaric, L., Zekic-Susac, M., Sarlija, N., & Vitale, B. (2010). Prediction of influenza vaccination outcome by neural networks and logistic regression. Journal of Biomedical Informatics, 43(5), 774-781.

Xiao, Y., Griffin, M. P., Lake, D. E., & Moorman, J. R. (2010). Nearest-neighbor and logistic regression analyses of clinical and heart rate characteristics in the early diagnosis of neonatal sepsis. Medical Decision Making, 30(2), 258-266.

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