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A survival analysis of patent rights using frailty models
Journal of the Korean Data & Information Science Society 2021;32:1155-69
Published online November 30, 2021;  https://doi.org/10.7465/jkdi.2021.32.6.1155
© 2021 Korean Data and Information Science Society.

Kineung Choo1 · Il Do Ha2

1Department of International Relations, Republic of Korea Naval Academy
2Department of Statistics, Pukyong National University
Correspondence to: 1 Professor, Department of International Relations, Republic of Korea Naval Academy, Changwon, 51702, Korea.
2 Corresponding author: Professor, Department of Statistics, Pukyong National University, Busan, 48513, Korea. E-mail: idha1353@pknu.ac.kr
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2020R1F1A1A01056987).
Received September 17, 2021; Revised October 2, 2021; Accepted October 3, 2021.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Using patent rights invented by doctoral graduates, this paper examines various survival analysis methods paying attention to the network characteristics of graduates. We compare among the results implemented by several R functions, and also compare them with results by the corresponding Stata commands. In a situation where multilevel frailties can be considered, there may be cases in which models having only one frailty term are selected. We compare the estimation results of the multi-level frailty model to ones with only a frailty term. This paper also compares how results from the parametric assumptions that the survival time of a patent right follows a known theoretical distribution differ from results of various semi-parametric models.
Keywords : Frailty, patent rights, parametric model, random effects, semi-parametric model, survival analysis.