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@article{171697,
        author = {Hirakant Chandrakant Yadav and Dr. Kishor Atkotiya},
        title = {Inferential Methods for Clinical Lifetime Models A SAS Implementation with Real-World Case Studies},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {854-862},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171697},
        abstract = {Lifetime models play a vital role in clinical research by helping to analyze the time until a specific event takes place. This paper examines inferential methods related to lifetime models, with an emphasis on their application within SAS. We present a comprehensive review of several inferential techniques, including Kaplan-Meier estimation, the Cox proportional hazards model, and parametric survival analysis. Furthermore, we illustrate the practical use of these methods through the analysis of actual clinical data in SAS.},
        keywords = {Lifetime models, Inferential techniques, Kaplan-Meier estimation, Cox proportional hazards model, parametric survival analysis, SAS.},
        month = {January},
        }