By embedding the missing covariate data into a left-truncated and right-censored survival model, we propose a new class of weighted estimating functions for the Cox regression model with missing covariates. The resulting estimators, called the pseudo-partial likelihood estimators, are shown to be consistent and asymptotically normal. A simulation study demonstrates that, compared with the popular inverse-probability weighted estimators, the new estimators perform better when the observation probability is small and improve efficiency of estimating the missing covariate effects. Application to a practical example is reported.
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http://dx.doi.org/10.1093/biomet/asp027 | DOI Listing |
Lifetime Data Anal
October 2024
University of Maryland, College Park, Maryland, United States.
Nested case-control design (NCC) is a cost-effective outcome-dependent design in epidemiology that collects all cases and a fixed number of controls at the time of case diagnosis from a large cohort. Due to inefficiency relative to full cohort studies, previous research developed various estimation methodologies but changing designs in the formulation of risk sets was considered only in view of potential bias in the partial likelihood estimation. In this paper, we study a modified design that excludes previously selected controls from risk sets in view of efficiency improvement as well as bias.
View Article and Find Full Text PDFStat Methods Med Res
August 2024
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Stat Med
March 2024
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
Accurate discrimination has been the central goal in identifying biomarkers for monitoring disease progression and early detection. Acknowledging the fact that discrimination accuracy of biomarkers for a time-to-event outcome often changes over time, local measures such as the time-dependent receiver operating characteristic curve and its area under the curve (AUC) are used to assess time-dependent predictive discrimination. However, such measures do not address subject heterogeneity, although the impact of covariates including demographics, disease-related characteristics, and other clinical information on the discriminatory performance of biomarkers needs to be investigated before their clinical use.
View Article and Find Full Text PDFInt J Cancer
April 2024
Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Infection by certain pathogens is associated with cancer development. We conducted a case-cohort study of ~2500 incident cases of esophageal, gastric and duodenal cancer, and gastric and duodenal ulcer and a randomly selected subcohort of ~2000 individuals within the China Kadoorie Biobank study of >0.5 million adults.
View Article and Find Full Text PDFStat Biosci
July 2023
Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston, 1200 Pressler St, Houston, TX 77030, USA.
Risk prediction models for survival outcomes are widely applied in medical research to predict future risk for the occurrence of the event. In many clinical studies, the biomarker data are measured repeatedly over time. To facilitate timely disease prognosis and decision making, many dynamic prediction models have been developed and generate predictions on a real-time basis.
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