Final Project Data Analysis Guidelines and Rubric

Running Head: Data Analysis Milestone Two: Describe the Data

DATA ANALYSIS

3-3 Final Project Data Analysis Milestone Two: Describe the Data

Maria Williams

Southern New Hampshire University

Biostatistics 21TW4

05/29/2021

Summary statistics

Column	n	Mean	Std. dev.	Median	Range	Min	Max	Q1	Q3
Age	100	68.25	14.42807	71	60	32	92	59.5	80.5
Gender	100	0.35	0.47937249	0	1	0	1	0	1

The total number of participants in this study was n=100. The mean age is 68.25 years, with a standard deviation of 14.42. The median age is 71 years with a range of 60. The lower quartile is 59.5, while the upper quartile is 80.5. On the other hand, the mean for gender is 0.35 with a standard deviation of 0.4793. The range value is 1 for gender.

Limitations

The key limitation is that the sample data is not representative enough to be generalized. Attention is focused on key aspects of "representativeness" and "generalizability" in both clinical and epidemiological studies (Sam et al., 2018). This is an encouraging trend, yet fundamental notions such as internal and external validity are often misrepresented, hiding the core difficulties of validity. In the text, the writers outline these difficulties and illustrate how they are interconnected and apply to other situations as well. Using real-world examples, they demonstrate ways in which distinct kinds of bias and confusion threaten validity. In addition, they include applicable concerns such as the selection of samples, exposures, and assessments, both in the clinic-based and population-based contexts.

Variables That Will Be Used

The study will focus on the significant factors of gender and age. Studies show that, after AMI, men's incidence of cardiac operations is much greater than that of women (Walli-Attaei et al., 2020). However, in certain cases, results indicate that there are no significant differences after accounting for age. Therefore, it is impossible to say whether or not a gender bias exists in cardiac treatment. To measure age-specific procedure rates by sex from administrative data, a population-based cohort technique will be utilized. Individual age-specific rates are most likely to show few significant variations by gender, and the age of intervention for both genders decreases dramatically after age twenty. When patient age is factored into the model, there is a substantial correlation between intervention rates and patient age, although sex is not. The striking gender gap in the overall AMI rates is obscured by the older age profile of women with AMI.

References

Sam, D., Gresham, G., Abdel-Rahman, O., & Cheung, W. Y. (2018). Generalizability of clinical trials of advanced melanoma in the real-world, population-based setting. Medical Oncology, 35(7), 1-8.

Walli-Attaei, M., Joseph, P., Rosengren, A., Chow, C. K., Rangarajan, S., Lear, S. A., ... & Yusuf, S. (2020). Variations between women and men in risk factors, treatments, cardiovascular disease incidence, and death in 27 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. The Lancet, 396(10244), 97-109.