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Table 1 Key quantities in estimation of Cox model parameters and their variance

From: Incorporating sampling weights into robust estimation of Cox proportional hazards regression model, with illustration in the Multi-Ethnic Study of Atherosclerosis

Cox PL

Influence Weights

Plus Sampling Weights

\(S^{(0)}(\beta,t) = \sum \limits _{j:t_{j} \geq t} e^{\beta ' z_{j}}\)

\(S_{r}^{(0)}(\beta,t) = \sum \limits _{j:t_{j} \geq t} A(t,z_{j}) e^{\beta ' z_{j}}\)

\(S_{wr}^{(0)}(\beta,t) = \sum \limits _{j:t_{j} \geq t} w_{j} A(t,z_{j}) e^{\beta ' z_{j}}\)

\(S^{(1)}(\beta,t) = \sum \limits _{j:t_{j} \geq t} z_{j} e^{\beta ' z_{j}}\)

\(S_{r}^{(1)}(\beta,t) = \sum \limits _{j:t_{j} \geq t} A(t,z_{j}) z_{j} e^{\beta ' z_{j}}\)

\(S_{wr}^{(1)}(\beta,t) = \sum \limits _{j:t_{j} \geq t} w_{j} A(t,z_{j}) z_{j} e^{\beta ' z_{j}}\)

\(S^{(2)}(\beta,t) = \sum \limits _{j:t_{j} \geq t} z_{j} z_{j}' e^{\beta ' z_{j}}\)

\(S_{r}^{(2)}(\beta,t) = \sum \limits _{j:t_{j} \geq t} A(t,z_{j}) z_{j} z_{j}' e^{\beta ' z_{j}}\)

\(S_{wr}^{(2)}(\beta,t) = \sum \limits _{j:t_{j} \geq t} w_{j} A(t,z_{j}) z_{j} z_{j}' e^{\beta ' z_{j}}\)

\(\bar {z}(\beta,t) = \frac {S^{(1)}(\beta,t)}{S^{(0)}(\beta,t)}\)

\(\bar {z}_{r}(\beta,t) = \frac {S_{r}^{(1)}(\beta,t)}{S_{r}^{(0)}(\beta,t)}\)

\(\bar {z}_{wr}(\beta,t) = \frac {S_{wr}^{(1)}(\beta,t)}{S_{wr}^{(0)}(\beta,t)}\)