Walden University Logistic Regression Discussion Paper – Description
Logistic regression is a statistical method for analyzing a dataset in which there are one or more independent variables that determine an outcome. Logistic Regression models are fit to an S-shared curve, as opposed to straight line of linear regression, because logistic regression models are binary classification models (they can only be used to distinguish between 2 different categories). Logistic regression is a common predictive model in clinical research and other medical and healthcare uses and has a wide range of applicability to such topics as variable selection, patient classification and response prediction. In this Discussion, you will run logistic regression analyses on NHANES data and consider how the model and results can positively impact social change.
TO PREPARE
Review the module Learning Resources.
Review Chapter 16 of the Warner (2021) textbook and the media program found in this week’s Learning Resources.
Create a research question using the National Health and Nutrition Examination Survey (NHANES) dataset that can be answered by multiple logistic regression. If necessary, you may need to search for the variable in the NHANES database found here:
Centers for Disease Control and Prevention. (2018). Search variables. https://wwwn.cdc.gov/nchs/nhanes/Search/default.aspx
Remember to select the proper release cycle (2015–2016). Then download the appropriate file and merge it with the available file from the resources.
Review the complex samples file available in the Learning Resources.
Consider a complex samples multiple logistic regression model that answers your research question.
Estimate a complex samples multiple logistic regression model that answers your research question.
BY DAY 4 OF WEEK 6
Post a response in which you:
Identify your research question, and explain the null hypothesis.
Interpret the Exp (B) coefficients for the model, specifically explaining the odds ratio and how you decided on the reference category for your independent variables.
Run diagnostics for the regression model, explaining what was run. Does the model meet all of the assumptions? Be sure and comment on what assumptions were not met and the possible implications. Is there any possible remedy for the assumption violations?
Create and explain an interaction term from two variables as this will be one of your explanatory, independent variables.
Explain how the model and results can positively impact social change.
References: You should support your work with evidence from scholarly resources that are current (e.g., less than five years old). However, there may be times when it is appropriate to cite seminal papers that helped shape the field of public health. Properly cite/reference using APA 7th edition.
The topic is: I have selected for monitoring is diabetes. Diabetes is a chronic disease characterized by high blood glucose levels, which can lead to various complications if not properly managed.
LEARNING RESOURCES
Warner, R. M. (2021). Multiple logistic regression. In Applied statistics II: Multivariable and multivariate techniques (3rd ed., pp. 583–624). Sage Publications.
Banerjee, S., & Panas, R. (2017). Diabetes and cardiorenal syndrome: Understanding the “triple threat.”, Hellenic Journal of Cardiology, 58(5), 342–347. https://doi.org/10.1016/j.hjc.2017.01.003
IBM. (2017). IBM SPSS complex samples 25,ftp://public.dhe.ibm.com/software/analytics/spss/documentation/statistics/25.0/en/client/Manuals/IBM_SPSS_Complex_Samples.pdf
UCLA Statistical Consulting Group. (n.d.). FAQ: How do I interpret odds ratios in logistic regression? https://stats.idre.ucla.edu/other/mult-pkg/faq/gen…
Walden University Academic Skills Center. (n.d.). Course-level statistics, https://academicguides.waldenu.edu/academic-skills…
Statistics Skills
Course Resources for RSCH8210
Course Resources for RSCH8260
Statistics Resources
SPSS/NVivo
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