Multiple Logistic Regression

Last week you explored categorical relationships including conditional probabilities, conditional odds, logits, odds ratios, relative risk, and slopes in the discussion. In the SPSS statistics assignment, you conducted a simple logistic regression analysis (one independent variable and one dependent variable) to begin to explore this statistical test and odds ratios. This week you start to fit models using multiple predictor variables that are continuous and categorical. As you learned with regression, you often need to construct models that move beyond bivariate analysis to control for other variables. In this sense, logistic regression is very similar except that you use a dichotomous outcome variable and interpret odds ratios rather than unstandardized coefficients.
Article Critique
The practice of quantitative research not only involves statistical calculations and formulas but also involves the understanding of statistical techniques related to real-world applications. You might not become a quantitative researcher nor use statistical methods in your profession but as a consumer, citizen, and scholar-practitioner, it will be important for you to become a critical consumer of research, which will empower you to read, interpret, and evaluate the strength of claims made in scholarly material and daily news.
For this Assignment, you will critically evaluate a scholarly article related to logistic regression.
Write a 2 page critique of the research you found that includes responses to the following:

Why did the authors select binary logistic regression in the research?
Do you think this test was the most appropriate choice? Why or why not?
Did the authors display the results in a figure or table?
Does the results table stand alone? In other words, are you able to interpret the study from it? Why or why not?
Resources:
Warner, R. M. (2013). Applied statistics: From bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: SAGE Publications.
Chapter 23, “Binary Logistic Regression” (pp. 1007–1050)
This chapter presents several simple examples of binary logistic regression. It also explains why researchers need to include probabilities along with odds when they report results

Possible article for review?
Adverse Childhood Experiences and Suicidality and Self-Harm in Persons in Secure Forensic Care
Jill D. Stinson, Alyssa P. Gretak, Rachel K. Carpenter and Megan A. Quinn Journal of the American Academy of Psychiatry and the Law Online December 2021, 49 (4) 553-564; DOI: https://doi.org/10.29158/JAAPL.210007-21