Table 3.
Multivariate analysis of COVID deaths
| Predictors | Estimate (b) | SE | t Stat | p value |
|---|---|---|---|---|
| (Intercept) | 85.1258 | 30.0668 | 2.8312 | 0.0051 |
| Tests per thousand | − 0.2288 | 0.1477 | − 1.5492 | 0.1229 |
| Stringency index | 0.5202 | 0.3479 | 1.4952 | 0.1364 |
| Population density | 0.0011 | 0.0073 | 0.1472 | 0.8831 |
| Median age | − 2.0553 | 1.1066 | − 1.8574 | 0.0647 |
| GDP per capita | 0.0018 | 0.0007 | 2.4233 | 0.0163 |
| Extreme poverty | − 1.0002 | 0.6836 | − 1.4631 | 0.1450 |
| Hospital beds/thousand | 1.2075 | 5.5085 | 0.2192 | 0.8267 |
| BCG Immunization | − 1.8233 | 0.3467 | − 5.2596 | 3.70e-07 |
| DTP3 Immunization | 1.8905 | 0.4680 | 4.0397 | 0.0001 |
Coefficient estimates (b) for a generalized linear regression of COVID deaths as responses on multiple predictors calculated using MATLAB glmfit function, with standard errors (SE), t statistics, and p values