Public Health Research

2

Data Analysis Plan

.

Jasmine Fields

Columbia Southern University

PUH 6301 Public Health Research

Dr. Lakina Moseley

April 4, 2023

Data Analysis Plan

Introduction

This research project focuses on vaccine hesitancy and its impact on public health. The study uses a mixed methods approach, including both quantitative and qualitative data collection methods. Statistical tests such as chi-square, logistic regression, and content analysis will be used to analyze and interpret the data collected.

How will you check for accuracy?

As the researcher conducting this study, I will be checking for accuracy through various methods. Firsttly, I will be ensuring that my data collection methods are reliable and valid by using established survey and interview tools. I will also be using a triangulation design to compare data from the quantitative and qualitative methods to validate and complement each other. Additionally, I will be using a multi-site approach to ensure external validity and make sure that my findings are applicable to a larger population. I will also be using a peer review process to validate my findings and ensure that they align with existing research on vaccine hesitancy. LastlyMoreover, I will maintain ethical considerations by obtaining informed consent from all participants and maintaining confidentiality throughout the research process (Dawadi et al., 2021).

Four Levels of Measurement

In my research project on vaccine hesitancy and its impact on public health, I will be using both quantitative and qualitative data collection methods. For the quantitative data, I will be using a survey tool will be used to gather information on vaccination rates, reasons for vaccine hesitancy, and demographic information such as age, gender, and education level. The data collected through the survey will be measured at the nominal level of measurement, as the responses will be categorical and cannot be ranked or ordered. However, the data can still be analyzed using valid statistical techniques such as frequency distributions and chi-square tests to determine if there are significant differences in vaccine hesitancy rates among different demographic groups. For the qualitative data collected through in-depth interviews and focus groups, the data will be measured at the ordinal level of measurement as responses will be ranked or ordered based on their level of agreement or importance. The data can be analyzed using valid statistical techniques such as content analysis to identify themes and patterns within the data (McLeod, 2019).

Collection of Variable Measurements & Type

IYes, in my research project on vaccine hesitancy and its impact on public health, I will be collecting variable measurements through the survey tool. The variables that I will be measuring include vaccination rates, reasons for vaccine hesitancy, and demographic information such as age, gender, and education level. These variables will be measured using categorical responses, such as yes or no for vaccination rates, and multiple-choice options for reasons for vaccine hesitancy and demographic information. Additionally, I will be collecting qualitative data through in-depth interviews and focus groups. The variable measurements in these methods will include the attitudes and beliefs of individuals who are hesitant or resistant to vaccines, as well as the experiences and perspectives of healthcare providers in addressing vaccine hesitancy. These variables will be measured using open-ended questions, allowing participants to provide detailed responses that can be categorized and analyzed. By collecting variable measurements through both quantitative and qualitative data collection methods, I will be able to gain a comprehensive understanding of vaccine hesitancy and its impact on public health, and identify potential solutions to improve vaccine acceptance.

Statistical Tests

In my research on vaccine hesitancy and its impact on public health, I will be using aA mixed methods approach will be used that includes both quantitative and qualitative data collection methods. To answer my research question, I will be using several statistical tests, including chi-square tests, logistic regression, and content analysis. I will use chi-square tests to determine if there are significant differences in vaccine hesitancy rates among different demographic groups. I will use logistic regression to explore the relationship between vaccine hesitancy and demographic variables such as age, gender, and education level (Pampel, 2020). Finally, I will use content analysis to identify themes and patterns within the qualitative data collected through in-depth interviews and focus groups. By using these statistical tests, I will be able to accurately analyze and interpret my data to gain a comprehensive understanding of vaccine hesitancy and its impact on public health. Proper data/statistical analysis is important in research as it allows for valid and reliable conclusions to be drawn from the data collected (Selvi, 2019). By using statistical tests such as chi-square and logistic regression, I will be able to determine if there are significant relationships between the variables being measured, and whether these relationships are statistically significant.

Consulting an Expert

I will consult with subject matter experts in the field of vaccine hesitancy and public health to gain additional insights and ensure that their research is up-to-date and relevant. Consulting with experts can provide valuable feedback on research design, data collection methods, and statistical analysis techniques. This feedback can help to improve the quality and validity of the research, ensuring that the findings are accurate and applicable to real-world situations.

References

Dawadi, S., Shrestha, S., & Giri, R. A. (2021). Mixed-methods research: A discussion on its types, challenges, and criticisms.  Journal of Practical Studies in Education,  2(2), 25-36.

McLeod, S. A. (2019). Qualitative vs. quantitative research.  Simply psychology,  30.

Pampel, F. C. (2020).  Logistic regression: A primer (No. 132). Sage publications.

Selvi, A. F. (2019). Qualitative content analysis. In  The Routledge handbook of research methods in applied linguistics (pp. 440-452). Routledge.