This article discusses the practical limitations of the flexible cure rate model proposed by Milienos (2022) in [
Citation: Diego I. Gallardo, Yolanda M. Gómez, Marcelo Bourguignon, Héctor J. Gómez. Reparameterized flexible cure models with direct interpretation via the lambert W function[J]. AIMS Mathematics, 2025, 10(9): 22249-22264. doi: 10.3934/math.2025991
This article discusses the practical limitations of the flexible cure rate model proposed by Milienos (2022) in [
| [1] |
F. S. Milienos, On a reparameterization of a flexible family of cure models, Stat. Med., 41 (2022), 4091–4111. https://doi.org/10.1002/sim.9498 doi: 10.1002/sim.9498
|
| [2] |
J. W. Boag, Maximum Likelihood Estimates of the Proportion of Patients Cured by Cancer Therapy, J. R. Stat. Soc. B, 11 (1949), 15–44. https://doi.org/10.1111/j.2517-6161.1949.tb00020.x doi: 10.1111/j.2517-6161.1949.tb00020.x
|
| [3] | A. Y. Yakovlev, A. D. Tsodikov, Stochastic Models of Tumor Latency and Their Biostatistical Applications, Singapore: World Scientific, 1996. https://doi.org/10.1142/2420 |
| [4] | A. D. Tsodikov, J. G. Ibrahim, A. Y. Yakovlev, Estimating Cure Rates from Survival Data: An Alternative to Two-Component Mixture Models, J. Am. Stat. Assoc. 98 (2003), 1063–1078. https://doi.org/10.1198/01622145030000001007 |
| [5] |
J. Rodrigues, M. De Castro, V. G. Cancho, N. Balakrishnan, COM–Poisson cure rate survival models and an application to a cutaneous melanoma data, J. Stat. Plan. Infer., 139 (2009), 3605–3611. https://doi.org/10.1016/j.jspi.2009.04.014 doi: 10.1016/j.jspi.2009.04.014
|
| [6] |
V. G. Cancho, F. Louzada, E. M. Ortega, The power series cure rate model: An application to a cutaneous melanoma data, Commun. Stat. Simul. Comput., 42 (2013), 586–602. https://doi.org/10.1080/03610918.2011.639971 doi: 10.1080/03610918.2011.639971
|
| [7] |
D. I. Gallardo, J. S. Romeo, R. Meyer, A simplified estimation procedure based on the EM algorithm for the power series cure rate model, Commun. Stat. Simul. Comput., 46 (2017), 6342–6359. https://doi.org/10.1080/03610918.2016.1202276 doi: 10.1080/03610918.2016.1202276
|
| [8] |
D. I. Gallardo, Y. M. Gómez, M. De Castro, A flexible cure rate model based on the polylogarithm distribution, J. Stat. Comput. Simul., 88 (2018), 2137–2149. https://doi.org/10.1080/00949655.2018.1451850 doi: 10.1080/00949655.2018.1451850
|
| [9] |
J. Rodrigues, V. G. Cancho, M. De Castro, F. Louzada-Neto, On the unification of long-term survival models, Stat. Probab. Lett., 79 (2009), 753–759. https://doi.org/10.1016/j.spl.2008.10.029 doi: 10.1016/j.spl.2008.10.029
|
| [10] | R. Corless, G. Gonnet, D. Hare, D. Jeffrey, D. Knuth, On the Lambert W function, Adv. Comput. Math., 5 (1996), 329–359. https://doi.org/10.1007/BF02124750 |
| [11] | Avraham Adler, lamW: Lambert-W Function, R package version 2.1.0, 2015. Available from: https://cran.r-project.org/web/packages/lamW/. |
| [12] | H. W. Borchers, pracma: Practical Numerical Math Functions, R package version 2.4.2, 2022. Available from: https://CRAN.R-project.org/package = pracma. |
| [13] | The R Foundation, R: A Language and Environment for Statistical Computing, 2025. Available from: https://www.R-project.org/. |
| [14] |
M. De Castro, V. G. Cancho, J. Rodrigues, A Bayesian Long-term Survival Model Parametrized in the Cured Fraction, Biometrical J., 51 (2009), 443–455. https://doi.org/10.1002/bimj.200800199 doi: 10.1002/bimj.200800199
|
| [15] | R. C. Mittelhammer, G. G. Judge, D. J. Miller, Econometric Foundations, New York: Cambridge University Press, 2000. |
| [16] | D. R. Cox, C. V. Hinkley, Theoretical Statistics, New York: Chapman and Hall/CRC, 1974. https://doi.org/10.1201/b14832 |
| [17] | E. L. Lehmann, The Power of Rank Tests, Ann. Math. Stat., 24 (1953), 23–43. https://doi.org/10.1214/aoms/1177729080 |
| [18] |
L. Hanin, L. Huang, Identifiability of cure models revisited, J. Multivar. Anal., 130 (2014), 261–274. https://doi.org/10.1016/j.jmva.2014.06.002 doi: 10.1016/j.jmva.2014.06.002
|
| [19] |
H. Akaike, A new look at the statistical model identification, IEEE T. Automat. Contr., 19 (1974), 716–723. https://doi.org/10.1109/TAC.1974.1100705 doi: 10.1109/TAC.1974.1100705
|
| [20] | G. Schwarz, Estimating the dimension of a model, Ann. Stat., 6 (1978), 461–464. |
| [21] |
T. H. Scheike, M. Zhang, Analyzing Competing Risk Data Using the R timereg Package, J. Stat. Software, 38 (2011), 1–15. https://doi.org/10.18637/jss.v038.i02 doi: 10.18637/jss.v038.i02
|