Biostatistician Needed for Historical Comparison of LAA Device Study Outcomes

Job ID: 38797791

Budget: $250 – $750 USD

I'm in need of an experienced biostatistician for a critical component of my thesis. The project involves a historical comparison of outcomes from a Left Atrial Appendage (LAA) device study.
I am seeking a professional statistical analysis to compare the outcomes of my study on the LAmbre LAA occlusion device with historical data from similar studies, such as those on the Watchman device. The analysis should include comparisons of procedural success rates, complication rates, residual leaks, and stroke recurrence rates. Please apply appropriate statistical tests, such as chi-square tests for categorical variables and t-tests for continuous variables, and provide confidence intervals for all key metrics.
If feasible, I request the use of propensity score matching to account for demographic differences (e.g., age and CHA2DS2-VASc scores) to ensure a balanced and meaningful comparison. Additionally, include visualizations (e.g., tables or charts) to clearly present the findings, along with a concise interpretation of how my study’s results compare to the historical data, highlighting any significant differences and their implications.
Key Requirements:
- The primary aim is to prepare the findings for publication in a scientific journal
- I am specifically looking for someone to assist with the statistical analysis of the data

Ideal Skills:
- Extensive experience in biostatistics and data analysis
- Prior experience contributing to scientific publications
- Strong understanding of LAA device studies and relevant outcomes

I am looking for someone who can not only analyze the data, but also help me interpret the results in a meaningful way for inclusion in the thesis.

The data primarily consists of quantitative measurements. Additionally, I require assistance with preparing the manuscript for publication. The analysis and manuscript preparation should be completed within 1 month. The demographic information includes age, sex, and comorbidities for propensity score matching.