Purpose
STATA is a software tool that is widely used in the field of statistics, econometrics, and epidemiology. It is particularly useful for data analysis in epidemiology, which is the study of the distribution and determinants of health-related states or events in specified populations.
Course Objectives
- Understanding the basics of STATA and its interface, including how to navigate the software and perform common tasks.
- Importing, cleaning, and manipulating data, including how to import data from different sources, identify and correct errors, and prepare data for analysis.
- Descriptive statistics and graphical representation, including how to calculate basic statistics and create various types of graphs to describe and summarize data.
- Bivariate and multivariate analysis, including how to use different statistical techniques such as chi-square tests, t-tests, and ANOVA to analyze relationships between variables.
- Hypothesis testing and statistical inference, including how to use STATA to perform hypothesis tests and make inferences about population parameters based on sample data.
- Advanced statistical methods such as survival analysis, logistic regression, and mixed-effects models, including how to use STATA to perform these advanced statistical techniques and interpret the results.
- Analysis of large datasets and survey data, including how to handle and analyze large datasets and survey data using STATA.
- Best practices for epidemiological data analysis, including how to plan and conduct effective epidemiological studies, ensure data quality and accuracy, and interpret and report results in a clear and appropriate manner.
- Hands-on practice and experience in data management, descriptive statistics, bivariate and multivariate analysis, hypothesis testing, advanced statistical methods and reporting using STATA.
- Application of STATA to different epidemiological research areas such as infectious diseases, chronic diseases, environmental epidemiology, and others.
Target Audience
- Epidemiologists, public health researchers and professionals, who are responsible for designing, conducting, and analyzing epidemiological studies.
- Researchers and professionals in fields such as biostatistics, medicine, veterinary medicine, and environmental health who use epidemiological data in their research and need to use STATA to analyze data.
- Graduate participant in fields such as epidemiology, biostatistics, and public health who need to learn how to use STATA for epidemiological data analysis.
- Researchers and professionals in non-profit organizations, government agencies, and research institutions who conduct epidemiological research and need to use STATA to analyze data.
- Medical statisticians and data analysts who are interested in epidemiology and want to learn how to use STATA for epidemiological data analysis.
- Anyone who is interested in epidemiology and wants to learn how to use STATA to analyze epidemiological data.
Program Outline
Topic 1. Introduction to STATA and its interface
Overview of STATA, its features and capabilities, and how to navigate the software and perform common tasks.
Topic 2. Importing, cleaning, and manipulating data
Importing data from different sources, identifying and correcting errors, and preparing data for analysis.
Topic 3. Descriptive statistics and graphical representation
Calculating basic statistics and creating various types of graphs to describe and summarize data.
Topic 4. Bivariate and multivariate analysis
Using different statistical techniques such as chi-square tests, t-tests, and ANOVA to analyze relationships between variables.
Topic 5. Hypothesis testing and statistical inference
Using STATA to perform hypothesis tests and make inferences about population parameters based on sample data.
Topic 6. Advanced statistical methods
Survival analysis, logistic regression, and mixed-effects models, Using STATA to perform these advanced statistical techniques and interpret the results.
Topic 7. Analysis of large datasets and survey data
Handling and analyzing large datasets and survey data using STATA.
Topic 8. Best practices for epidemiological data analysis
Planning and conducting effective epidemiological studies, ensuring data quality and accuracy, and interpreting and reporting results in a clear and appropriate manner.
Topic 9. Hands-on practice and experience
Data management, descriptive statistics, bivariate and multivariate analysis, hypothesis testing, advanced statistical methods and reporting using STATA.
Topic 10. Advanced topics
Advanced statistical methods such as Cox regression, GEE, and mixed-effects models, dealing with missing data, advanced graphing, advanced data visualization, and others.
Topic 11. Application of STATA
Application to different epidemiological research areas such as infectious diseases, chronic diseases, environmental epidemiology, and others.