Efficient Estimation of Fixed and Time‐varying Covariate Effects in Multiplicative Intensity Models

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On the Cox Model With Time-Varying Regression Coefficients (2005, methodology): “Furthermore, B̂(t) has the same limiting distribution as that of the sieve estimator proposed by Murphy and Sen (1991), which is semiparametric efficient for B0(t) (Martinussen et al.”
On Estimation and Tests of Time‐Varying Effects in the Proportional Hazards Model (2004, methodology): “The model (3) was studied in detail in the case where the baseline hazard was k0(t) was included in the exponent of the model by Martinussen et al. (2002).”
Efficient Estimation in Marginal Partially Linear Models for Longitudinal/Clustered Data Using Splines (2007, methodology): “Martinussen et al. (2002) considered the partially linear model in the context of Cox’s regression model for survival data.”
An Additive–Multiplicative Cox–Aalen Regression Model (2002, unknown): “Martinussen et al. (2001) considered this model as well as the semiparametric submodel where some covariate effects do not vary with time and focused on estimation of cumulative effects.”