Model estimates from Shenzhen Bayesian Logistic Regression

A list containing components of the Bayesian logistic model fit to the Shenzhen Data

shenzhen_model_estimates

Format

A list with 8 compoments, each with 5,000 observations for the 5,000 runs:

beta_0

The intercept from the logistic regression model

beta_1

Coefficient for the first component of the polynomial term in the logistic regression model

beta_2

Coefficient for the second component of the polynomial term in the logistic regression model

beta_3

Coefficient for the third component of the polynomial term in the logistic regression model

mu

Predicted values from the logistic regression model

sens

Sensitivity estimate from the logistic regression model

log_lik

Log likelihood from the logistic regression model

lp__

Log density up to a constant

Source

Zhang, Z. et al. Insights into the practical effectiveness of RT-PCR testing for SARS-CoV-2 from serologic data, a cohort study. doi:10.1101/2020.09.01.20182469.

Kucirka, L. M., Lauer, S. A. & Laeyendecker, O. Variation in false-negative rate of reverse transcriptase polymerase chain reaction–based SARS-CoV-2 tests by time since exposure. Ann. Intern. Med. (2020)