Assignment: Logistic Regression in Nursing Practice

Assignment: Logistic Regression in Nursing Practice

Assignment: Logistic Regression in Nursing Practice

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Logistic Regression in Nursing Practice

Logistic regression is used to analyze a wide variety of variables that may surround a singular outcome. For example, logistic regression could be used to identify the likelihood of a patient having a heart attack or stroke based on a variety of factors including age, sex, genetic characteristics, weight, and any preexisting health conditions. The biological systems and issues with which the health care field is concerned represent the kinds of applications for which logistic regression is especially useful.

Logistic regression is used in the health care field for many purposes, including diagnoses, predictions, and forecasting. The three articles in this week’s Learning Resources illustrate the many uses of logistic regression in the health care field. This Discussion allows you to explore the different uses of logistic regression and cultivate a deeper understanding of the application of logistic regression in evidence-based 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?
By Thursday 10/12/17, 5 pm, write a minimum of 550 words essay in APA format. Use at least 3 references from the list of required reading below. Include the level one headings as numbered below.

Post a cohesive response that addresses the following:

1) In the first line of your posting, identify the article you examined, providing its correct APA citation. (See attached PDF file for the article).

2) Post your critical analysis of the article as outlined above (make sure to answer all the points asked above in the “To Prepare” area, bullets [1, 2, 3]).

3) Propose potential remedies to address the weaknesses of each study (bullets 4 and 5 in the “To Prepared” area).

4) Analyze the importance of this study to evidence-based practice, the nursing profession, or society (bullet 6 in the “To Prepared” area).

Learning Resources

.

Required Media

“Multiple Regression”

Used by permission from SPSS VideoTutor.com A division of Consumer Raters LLC., 1121 S Military Trail, 314, Deerfield Beach, FL 33442, USA

Note: The approximate length of this media piece is 5 minutes.

“Logistic Regression”

Used by permission from SPSSVideoTutor.com A division of Consumer Raters LLC., 1121 S Military Trail, 314, Deerfield Beach, FL 33442, USA

Note: The approximate length of this media piece is 15 minutes.

Required Readings

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”

This chapter asserts that predictive analyses are based on probability theory instead of decision theory. It also analyzes how variation plays a critical role in simple linear regression and multiple regression.

Statistics and Data Analysis for Nursing Research

Chapter 9, “Correlation and Simple Regression” (pp. 208–222)

This section of Chapter 9 discusses the simple regression equation and outlines major components of regression, including errors of prediction, residuals, OLS regression, and ordinary least-square regression.

Chapter 10, “Multiple Regression”

Chapter 10 focuses on multiple regression as a statistical procedure and explains multivariate statistics and their relationship to multiple regression concepts, equations, and tests.

Chapter 12, “Logistic Regression”

This chapter provides an overview of logistic regression, which is a form of statistical analysis frequently used in nursing research.

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. doi:10.2105/AJPH.2009.190892

This article discusses the results of a study of how many U.S. farmworkers accessed U.S. health care. The study considered this question on several levels—individual, environmental, and policy—and used logistic regression to analyze the multivariate data gathered.

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. doi:10.1016/j.jbi.2010.04.011.

This article describes the methods and results of a neural network study on the effectiveness of the influenza vaccine using historical data in three neural network algorithms. The article also provides a discussion of logistic regression in comparison to the neural network algorithms used.

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. doi:10.1177/0272989X09337791

This article outlines the procedures and findings of a study on the use of two methods of neonatal sepsis diagnosis: nearest-neighbor analysis and logistic regression analysis. The results indicated that each method generates unique information useful to diagnosis, and therefore both methods should be used simultaneously for improved accuracy of diagnoses.

Optional Resources

Walden University. (n.d.). Linear regression. Retrieved August 1, 2011, from http://streaming.waldenu.edu/hdp/researchtutorials/educ8106_player/educ8106_linear_regression.html

attachment
logisticregressionArticle.pdf

You must proofread your paper. But do not strictly rely on your computer’s spell-checker and grammar-checker; failure to do so indicates a lack of effort on your part and you can expect your grade to suffer accordingly. Papers with numerous misspelled words and grammatical mistakes will be penalized. Read over your paper – in silence and then aloud – before handing it in and make corrections as necessary. Often it is advantageous to have a friend proofread your paper for obvious errors. Handwritten corrections are preferable to uncorrected mistakes.

Use a standard 10 to 12 point (10 to 12 characters per inch) typeface. Smaller or compressed type and papers with small margins or single-spacing are hard to read. It is better to let your essay run over the recommended number of pages than to try to compress it into fewer pages.

Likewise, large type, large margins, large indentations, triple-spacing, increased leading (space between lines), increased kerning (space between letters), and any other such attempts at “padding” to increase the length of a paper are unacceptable, wasteful of trees, and will not fool your professor.

The paper must be neatly formatted, double-spaced with a one-inch margin on the top, bottom, and sides of each page. When submitting hard copy, be sure to use white paper and print out using dark ink. If it is hard to read your essay, it will also be hard to follow your argument.

 

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