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1712068PublishedVol 9 · Issue 5

Statistical Modelling of Bladder Cancer Remission Data of Fluctuating Hazard Rate: An Inverse Power Pranav Distribution Approach

Chinedu Kingsley Nwankwo Blessing Agbo Chiemerie Nwokemodo Joshua O. Adeniran

Subject area: Physical Sciences and Environment  ·  Area of research: Biostatistical Study in Survival Analysis

DOI: https://doi.org/10.64388/IREV9I5-1712068

Abstract

This study introduces the Inverse Pranav Distribution (IPD) as a flexible model for survival data with both monotone and non-monotone hazard rate behaviors. The Pranav distribution was inversely transformed to create the model, and its main statistical characteristics were determined. Using data on bladder cancer patients' remission times, the IPD's performance was contrasted with that of the Inverse Rama, Inverse Lindley, Inverse Exponential, and Inverse XGamma distributions. Based on likelihood values, information criteria, and goodness-of-fit tests, the results indicated that the IPD offered the best overall fit, outperforming rival models. The distribution was appropriate for survival and reliability studies because it could capture intricate hazard structures, including decreasing, increasing, and bathtub-shaped patterns.

Keywords

Bladder Cancer, Inverse Power Pranav

How to cite this paper

Chinedu Kingsley Nwankwo, Blessing Agbo, Chiemerie Nwokemodo, Joshua O. Adeniran "Statistical Modelling of Bladder Cancer Remission Data of Fluctuating Hazard Rate: An Inverse Power Pranav Distribution Approach" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 1435-1444 https://doi.org/10.64388/IREV9I5-1712068
Chinedu Kingsley Nwankwo, Blessing Agbo, Chiemerie Nwokemodo, Joshua O. Adeniran "Statistical Modelling of Bladder Cancer Remission Data of Fluctuating Hazard Rate: An Inverse Power Pranav Distribution Approach" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025, doi: https://doi.org/10.64388/IREV9I5-1712068
Chinedu Kingsley Nwankwo, Blessing Agbo, Chiemerie Nwokemodo, Joshua O. Adeniran (2025). Statistical Modelling of Bladder Cancer Remission Data of Fluctuating Hazard Rate: An Inverse Power Pranav Distribution Approach. Iconic Research And Engineering Journals, 9(5). doi: https://doi.org/10.64388/IREV9I5-1712068
Chinedu Kingsley Nwankwo, Blessing Agbo, Chiemerie Nwokemodo, Joshua O. Adeniran "Statistical Modelling of Bladder Cancer Remission Data of Fluctuating Hazard Rate: An Inverse Power Pranav Distribution Approach" Iconic Research And Engineering Journals, vol. 9, no. 5, Nov. 2025. Crossref, https://doi.org/10.64388/IREV9I5-1712068
@article{1712068,
      author = {Chinedu Kingsley Nwankwo, Blessing Agbo, Chiemerie Nwokemodo, Joshua O. Adeniran},
      title = {Statistical Modelling of Bladder Cancer Remission Data of Fluctuating Hazard Rate: An Inverse Power Pranav Distribution Approach},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {5},
      pages = {1435-1444},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712068.pdf},
      abstract = {This study introduces the Inverse Pranav Distribution (IPD) as a flexible model for survival data with both monotone and non-monotone hazard rate behaviors. The Pranav distribution was inversely transformed to create the model, and its main statistical characteristics were determined.  Using data on bladder cancer patients' remission times, the IPD's performance was contrasted with that of the Inverse Rama, Inverse Lindley, Inverse Exponential, and Inverse XGamma distributions.  Based on likelihood values, information criteria, and goodness-of-fit tests, the results indicated that the IPD offered the best overall fit, outperforming rival models.  The distribution was appropriate for survival and reliability studies because it could capture intricate hazard structures, including decreasing, increasing, and bathtub-shaped patterns.},
      keywords = {Bladder Cancer, Inverse Power Pranav},
      month = {November},
      doi = {https://doi.org/10.64388/IREV9I5-1712068}
  }