Spatial Modeling Weibull-3 Survival Parameters with Frailty Distributed Conditionally Autoregressive (CAR)

Nur Mahmudah, Henny Pramoedyo

Abstract


Survival analysis is a collection of statistical procedures for data analyzing, where respon variables caused by time until an event occurs. One of application of survival regression’s purpose is to know dengue hemorragic fever. Since the spread of dengue hemorragic fever caused by the spread of mosquito, there is probability that event in one location affects other event in another locations thus, it is better to model with Bayessian method of spatial survival. Model includes random spatial effect CAR to overcome the spatial effect in survival model using queen contiguity type weight. This study aimed to obtain spatial survival model one survival data year of 2013 which was the event of dengue hemorragic fever in city of Malang. Based on the data, moran value I was -0.5930 with Z-test value equal to -2,002, which means there is a spatial autocorelation on the event of dengue hemorragic fever in city of Malang. Spatial survival model with Weibull-3 Parameter (Weibull-3P) distribution obtained the factors significantly affecting dengue hemorragic fever, which were sex, hematrocit rate, thrombocyte volume had equal rate of healing in each subdistrict. 

 


Keywords


dengue hemorragic fever; Bayessian; spatial survival Weibbul-3P, frailty distributed conditionally autoregresive (CAR); queen contiguity and Moran’s I

Full Text:

PDF

References


Aksioma, D.F. (2012), Model Spasial Survival Weibull-3P dengan Pendekatan Bayessian dan Aplikasinya Pada WinBUGS, Genetika 2: 94-105.

Aksioma, D.F. & N. Iriawan (2010), Spatial Autocorrelation of the DHF Outbreaks in the City of Surabaya, Proceeding of The Third International Conference on Mathematics and Natural Sciences (ICMNS) 2010, Bandung.

Amalia, S. (2010), Analisis Survival dan Faktor-Faktor yang Mempengaruhi Pasien Demam Berdarah dengan Menggunakan Bayesian Mixture, Tugas Akhir (Tidak Dipublikasikan), Insitut Teknologi Sepuluh November, Surabaya.

Banerjee, S., Wall, M. M., and Carlin, B. P (2003), Frailty Modeling for Spatially Correlated Survival Data, With Application To Infant Mortality in Minnesota, Biostatistics 1:123-142.

Box, G. E. P. Dan Tio (1973), Bayesian Inference in Statistical Analysis, Reading, MA: Addison-wesley.

Darmofal, D. (2008), Bayesian Spatial Survival Models for Political Event Processes, Departemen of Political Science, University of South Carolina, 350 Gambrell Hall, Columbia.

Hasyim, M. (2012), Model mixture survival spasial dengan frailty berdistribusi conditionally autoregrresive (CAR). Tesis. Insitut Teknologi Sepuluh November, Surabaya.

Klienbum, D.G. and Klien, M. (2005), Survival Analysis, A Self-Learning Text, Springer Science Bussiness Media, Inc., USA.

Lee, J. and Wong, D.W.S. (2001), Statistical Analysis with Arcview GIS, John Wiley and Sons, Inc., New York.

Ntzoufras, I. (2009), Bayesian Modeling Using WinBUGS, John Wiley & Sons, Inc., USA.




DOI: http://dx.doi.org/10.21776/ub.natural-b.2015.003.01.12

Refbacks

  • There are currently no refbacks.