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Maximum likelihood inference for the Cox regression model with applications to missing covariates
2009
In this paper, we carry out an in-depth theoretical investigation for existence of maximum likelihood estimates for the Cox model (Cox, 1972, 1975) both in the full data setting as well as in the presence of missing covariate data. The main motivation for this work arises from missing data problems, where models can easily become difficult to estimate with certain missing data configurations or large missing data fractions. We establish necessary and sufficient conditions for existence of the
doi:10.17615/7kq2-jr80
fatcat:bwrk3uv3ujhknhd7xqitn626ci