InstructionsOverview/Description: My specialization is MSN-APRN in Family Nurse Practitioner, Make sure the entire project is centered in one topic only. The final project for NSG6101 consists of the

Running Head: RESEARCH PROPOSAL DATA ANALYSIS PLAN 0

Research Proposal Data Analysis Plan

Yulak Landa

Dr. Sandra Allen

May 7, 2020

The primary study outcome is to determine the efficacy of the respiratory masks as compared to standard masks under high-risk exposure in a healthcare setting. The demographic and study variables will be analyzed. The analysis will involve the collection and organization of study data to assist in drawing up of verifiable conclusions from the data. To achieve the outcomes, I will employ the descriptive statistical techniques as well as inferential statistical approaches (Mihaela Coroiu, Delia Calin, & Nutu, 2019).

Descriptive statistics will be of great importance when it comes to analyzing the demographic characteristics. At the end of the intervening period, the number of practitioners who will have contacted the virus will be taken. This data will be summarized based on the age, gender, and mask used just as how we grouped them in the sample making process. The arithmetic mean will be calculated based on those characteristics. I also look forward to utilizing the SSPS software to assist me in obtaining relevant frequency distribution tables to bring out the trend of infections (Gauer & Jackson, 2018).

The variables for the study will include the adherence to the set-out standards of hand hygiene and related protections, and the type of mask used whether respiratory mask or the standard masks. The relationship between the results of nostrils swabs and pharynx swabs will also be observed. The spearman's rank correlation coefficient and the dot diagram will be used to compare the correlation between the results of nasal swabs and that of pharynx swabs. The univariate Tobit regression model will be used to investigate the factors behind any disparity in the outcomes of the two masks (Han & Cho, 2018). This analysis will help us to make the inferences on whether surgical masks are better and more efficient than standard masks.

References

Gauer, J., & Jackson, J. B. (2018). Relationships of demographic variables to USMLE physician licensing exam scores: A statistical analysis on five years of medical student data. Advances in Medical Education and Practice, Volume 9, 39-44. doi:10.2147/amep.s152684

Han, J., & Cho, H. (2018). A study on cluster analysis of mixed data with continuous and categorical variables. The Korean Medical Data Analysis Society, 20(4), 1769-1780. doi:10.37727/jkdas.2018.20.4.1769

Mihaela Coroiu, A., Delia Calin, A., & Nutu, M. (2019). Topic modeling in medical data analysis. Case study based on medical records analysis. 2019 International Conference on Software, Telecommunications, and Computer Networks (SoftCOM). doi:10.23919/softcom.2019.8903900