Data Analysis for a comparative retrospective cohort study with longitudinal data

We are conducting a comparative retrospective cohort study with longitudinal data. We are seeking an experienced data analyst to work with our data file in R Studio, focusing on comprehensive analysis without further data collection. The analysis will provide insights into acute and long-term outcomes across groups, helping to inform our thesis research.

The compensation for this project is set at 150 euro, with the price negotiable based on expertise, payable upon delivery,with a preferred delivery timeframe of 2 days. Further project details will be provided upon selection. The chosen candidate will need to sign a confidentiality contract before proceeding.

Scope of Work:

-Perform descriptive analysis to summarize key characteristics of the data.
-Conduct between-group and within-group analyses to explore changes and differences in outcomes.
-Apply inferential statistical tests, such as t-tests or chi-square tests, to assess differences in outcomes between groups.
-Use regression analysis to control for potential confounders and assess the impact of specific variables.
-Conduct two distinct analyses: one focusing on acute outcomes and the other on long-term outcomes.
-Analyze one variable separately to examine its specific impact on outcomes.
- Generate comprehensive visualizations to illustrate key findings.
- Conduct tests to confirm the assumptions underlying inferential statistical tests.
- Address missing data appropriately using imputation or other statistical techniques.

Ideal Skills and Experience:

-Expertise in R Studio for data analysis, particularly with healthcare and longitudinal data.
-Experience in performing both descriptive and inferential statistical analyses on cohort study data.
-Proficiency in applying t-tests, chi-square tests, and regression analysis for confounder adjustment.
-Strong analytical skills for identifying insights from complex datasets.

We are seeking a skilled analyst to conduct a thorough analysis and provide the R code used, along with the R output, visualizations. If you have the expertise and background to contribute meaningfully to our study, we would greatly appreciate your collaboration.

Please include line plots (to better visualize the outcomes),Paired Box Plots (to compare baseline and follow-up values for each metric) etc