A recent NEJM paper: Risk Factors, Mortality, and Cardiovascular Outcomes in Patients with Type 2 Diabetes
Design: Cohort study- based on registry data
Exposed: diabetes ; non-exposed: no diabetes
FU ~ 5 yr
Outcomes: all-cause and CVD types mortality
They matched ~ 270K diabetes patients with ~ 1.3 million no-diabetes ppl
What could be the reasons for matching? Confounding control can easily be done with regression. Statistical efficiency and precision? necessary with such large sample size?
They report “relative importance of risk factors in predicting outcomes” as measured by R squared and “explainable log-likelihood”.
What are the relative merits of standardized coefficients vs. R sq – vs LRT?
Thank you for your thoughts.