Discussion 2: Logistic Regression in Nursing Practice

Walden University Discussion 2: Logistic Regression in Nursing Practice-Step-By-Step Guide

This guide will demonstrate how to complete the Walden University Discussion 2: Logistic Regression in Nursing Practice assignment based on general principles of academic writing. Here, we will show you the A, B, Cs of completing an academic paper, irrespective of the instructions. After guiding you through what to do, the guide will leave one or two sample essays at the end to highlight the various sections discussed below.

How to Research and Prepare for Discussion 2: Logistic Regression in Nursing Practice

Whether one passes or fails an academic assignment such as the Walden University Discussion 2: Logistic Regression in Nursing Practice depends on the preparation done beforehand. The first thing to do once you receive an assignment is to quickly skim through the requirements. Once that is done, start going through the instructions one by one to clearly understand what the instructor wants. The most important thing here is to understand the required format—whether it is APA, MLA, Chicago, etc.

After understanding the requirements of the paper, the next phase is to gather relevant materials. The first place to start the research process is the weekly resources. Go through the resources provided in the instructions to determine which ones fit the assignment. After reviewing the provided resources, use the university library to search for additional resources. After gathering sufficient and necessary resources, you are now ready to start drafting your paper.

How to Write the Introduction for Discussion 2: Logistic Regression in Nursing Practice

The introduction for the Walden University Discussion 2: Logistic Regression in Nursing Practice is where you tell the instructor what your paper will encompass. In three to four statements, highlight the important points that will form the basis of your paper. Here, you can include statistics to show the importance of the topic you will be discussing. At the end of the introduction, write a clear purpose statement outlining what exactly will be contained in the paper. This statement will start with “The purpose of this paper…” and then proceed to outline the various sections of the instructions.

How to Write the Body for Discussion 2: Logistic Regression in Nursing Practice

After the introduction, move into the main part of the Discussion 2: Logistic Regression in Nursing Practice assignment, which is the body. Given that the paper you will be writing is not experimental, the way you organize the headings and subheadings of your paper is critically important. In some cases, you might have to use more subheadings to properly organize the assignment. The organization will depend on the rubric provided. Carefully examine the rubric, as it will contain all the detailed requirements of the assignment. Sometimes, the rubric will have information that the normal instructions lack.

Another important factor to consider at this point is how to do citations. In-text citations are fundamental as they support the arguments and points you make in the paper. At this point, the resources gathered at the beginning will come in handy. Integrating the ideas of the authors with your own will ensure that you produce a comprehensive paper. Also, follow the given citation format. In most cases, APA 7 is the preferred format for nursing assignments.

How to Write the Conclusion for Discussion 2: Logistic Regression in Nursing Practice

After completing the main sections, write the conclusion of your paper. The conclusion is a summary of the main points you made in your paper. However, you need to rewrite the points and not simply copy and paste them. By restating the points from each subheading, you will provide a nuanced overview of the assignment to the reader.

How to Format the References List for Discussion 2: Logistic Regression in Nursing Practice

The very last part of your paper involves listing the sources used in your paper. These sources should be listed in alphabetical order and double-spaced. Additionally, use a hanging indent for each source that appears in this list. Lastly, only the sources cited within the body of the paper should appear here.

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Discussion 2: Logistic Regression in Nursing Practice

Introduction

According to Polit (2010), the definition of logistic regression is “it analyzes the relationship between multiple independent variables and a single dependent variable, and yields a predictive equation (Pg. 306).” What make logistic regression useful are the biological systems and issues with which the health care field is concerned. We use logistic regression in healthcare to diagnose, predict, and forecast what could happen to patients.

Article Selection of Interest

“Prediction of influenza vaccination outcome by neural networks and logistic regression.”

Tritica-Majnaric, L., Zekic-Susac, M., Sarlija, N., and 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

Critical Analysis of Article

What are the goals and purposes of the research study the article describes? The purpose of the study was to design a computer-based neural network model that will enable successful prediction of the outcome of influenza vaccine efficacy based on data related to influenza viruses and influenza vaccination, in combination with historical medical data (Tritica-Majnaric at al, 2010). The aim of the study was to design an intelligent computer-based neural network model that will enable successful prediction of the outcome of influenza vaccine efficacy (Tritica-Majnaric at al, 2010).

How is logistic regression used in the study? What are the results of its use? Logistic regression modeling is widely used for analyzing

Discussion 2 Logistic Regression in Nursing Practice

multivariate data providing a powerful technique analogous to multiple regression and ANOVA for continuous responses (Tritica-Majnaric at al, 2010). The likelihood function of mutually independent variables Y1,…,Yn with outcomes measured on a binary scale is a member of the exponential family with (log(π11-π1),…,log(πn1-πn)) as a canonical parameter (πj is a probability that Yj becomes 1), the assumption of the logistic regression model is a linear relationship between a canonical parameter and the vector of explanatory variables x_j(Tritica-Majnaric at al, 2010)_.Three algorithms and logistic regression were used in order to provide the influenza vaccination probability model that could be used for prediction purposes in the practice of primary health care physicians, where the vaccine is usually dispensed (Tritica-Majnaric at al, 2010).

What other quantitative and statistical methods could be used to address the research issue discussed in the article? Cross-validation was used in this paper because it produces no statistical bias of the result since each tested sample is not a member of the training set (Tritica-Majnaric at al, 2010). Others used are neural network methodology, logistic regression methodology, and evaluating model performance (Tritica-Majnaric at al, 2010).

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What are the strengths and weaknesses of the study? The main challenge is to predict which individual will most likely adequately respond to conventional influenza vaccines and which individual will not (Tritica-Majnaric at al, 2010). The artificial neural networks (ANN) have been shown to be a suitable computer-based method which can incorporate non-linear effects and interactions between multiple variables in a valid probability model (Tritica-Majnaric at al, 2010). The model is based on the results of vaccination by the influenza vaccine strain, the content of which was recently changed and on which, therefore, a poor antibody response was expected (Tritica-Majnaric at al, 2010). The results were compared with a standard logistic regression approach (Tritica-Majnaric at al, 2010). The major challenge in influenza vaccination is to predict vaccine efficacy (Tritica-Majnaric at al, 2010).

How could the weaknesses of the study be remedied? One way of remediating the weakness of the study is to use a larger sample size. Another way is to continue testing the influenza vaccine until the most accurate one becomes available.

How could findings from this study contribute to evidence-based practice, the nursing profession, or society? It gives a prediction of the outcome of influenza vaccination based on real historical medical data.

Conclusion

The influenza vaccination is fascinating to me in that hopefully one day, there will be a universal vaccination that covers all strains and maybe a person only has to get it once every five years or so. The importance of the study is that it continues to be researched to find that one vaccine to cover everyone.

References

Gray, J.R., Grove, S.K., and Sutherland, S. (2017). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (9^th ed.). Saunders Elsevier.

Polit, D.F. (2010). Statistics and Data Analysis for Nursing Research (2^nd Ed.). Pearson Education Inc., Upper Saddle River, New Jersey.

Tritica-Majnaric, L., Zekic-Susac, M., Sarlija, N., and 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