PleaseI want to do for me this project (note: you need to have R/R Studio for analysis): analysis and interpretation of a secondary dataset to test a health economic hypothesis. The dataset is uploaded.

Other details:

Learning outcomes to be assessed – you should be able to: · Show an in-depth understanding of the application of statistical techniques to health data · Show an in-depth understanding of the use of quasi experimental designs · Critically examine different regression models · Apply statistical techniques using standard econometric software · Develop an economic hypothesis and understand the appropriate statistical methods required to test the hypothesis You should conduct your analysis in R/RStudio using the following dataset (an extract from Chile EPS).

Your analysis should be limited to the latest wave of data for the year 2009 only and you should employ cross sectional methods. Pardo, Cristian (2019), “Data for: Health Care Reform, Adverse Selection and Health Insurance Choice”, Mendeley Data, V1, doi: 10.17632/5dw4gxyh93.1 The Social Protection Survey (EPS) is the largest and oldest longitudinal survey that exists in Chile, with a sample of around 16,000 respondents distributed in all regions of the country. The questionnaire includes questions on labour and social security with detailed information in areas such as education, health, social security, job training, wealth and assets, family history and household information. In this dataset there are 9 variables:

1. folio – a participant ID 2. Age (in years) 3. Female (0= male/1= female)
4. Edu_yrs (years of education) 5. Ins (insurance: 1 = private, 2 = public, 3 = none) 6. Hlstat (Health status 1= best, 5= worst) 7. R_incomeall (income in Chilean peso) 8. Survey (year of data survey) 9. N_depend (number of dependents).

You should make sure to cover the following steps in your analysis: · Develop a health economic hypothesis of a relationship between two of the variables in the dataset, supported by some outside literature or empirical research (make sure to include appropriate references) · Describe and justify how you will test this hypothesis – you should employ both bivariate and multivariate methods (Note: remember only data for year 2009) · Consider the level of missing data and appropriate methods for handling it · Present relevant descriptive statistics (Note: remember only data for year 2009) · Perform appropriate modelling/statistical tests to refute or support the hypothesis · Critically examine the results of your analyses · Consider the strengths and limitations of your methods and how other study design or analytical techniques could help address your hypothesis o What is this analysis not able to tell us? Think about causality. o Is there potential bias? o Are there other longitudinal methods that could be used?

Your final submission is a written report of up to 2,000 words:

i. The report must include the following components based on your analysis: • Introduction – introduce your empirical analysis, why it might be relevant to health policy, and establish how it will help us test an economic hypothesis (guide: ~250 words) • Methods – Describe the data and methods you have used to perform your analysis. Make sure to briefly cover why these methods have been chosen – critically engaging with the statistical methods that could be used is paramount. Make sure you address both descriptive and inferential techniques (guide: ~650 words) • Results – Detail your empirical findings clearly with appropriate use of tables and figures (guide: ~600 words) • Discussion – succinctly discuss the issues in the data, what the results mean and any strengths and limitation of your analysis (guide: ~350 words) • Conclusions – succinctly present in a few points what can be concluded based on your analysis (guide: 150 words) • References – use consistently and as per the referencing guidance

ii. Use appropriate academic referencing, using Harvard referencing style

iii. You may choose to present tables or figures to support your analysis – ensure they are legible and contribute to your analysis. Although tables and figures do not count towards 2000-word limit, only use tables and figures if they are essential to support your analysis. You can also use up to 2 appendices. Redundant data presented in tables and figures are not welcome.
iv. You should make good use of the word length to produce a thorough empirical analysis.

Helpful resources:

• Harrison, E. and Pius, R., 2020. R for Health Data Science. Chapman and Hall/CRC. • (https://argoshare.is.ed.ac.uk/healthyr_book/) • Data Analytics with R. Adam Smith, UCL School of Management. https://www.adamnsmith.com/MSIN0010/index.html • Gujarati, D. N. (2009) Essentials of econometrics. New York: Sage. • Gujarati, D. N. (2015) Econometrics by example. 2nd edn. New York: Palgrave Macmillan.