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DESAK PUTU PRAMI MEITRIANI
Faculty of Mathematics and Natural Sciences, Udayana University
Mathematics

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PENERAPAN REGRESI QUASI-LIKELIHOOD PADA DATA CACAH (COUNT DATA) YANG MENGALAMI OVERDISPERSI DALAM REGRESI POISSON DESAK PUTU PRAMI MEITRIANI; KOMANG GDE SUKARSA; I PUTU EKA NILA KENCANA
E-Jurnal Matematika Vol 2 No 2 (2013)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2013.v02.i02.p036

Abstract

Poisson regression can be used to analyze count data, with assuming equidispersion. However, in the case of overdispersion often occur in the count data. The implementation of Poisson Regression can not be applied on this data because the data having overdispersion, that will lead to underestimate the standard error. Thus, use Quasi-Likelihood regression on this data. Quasi-Likelihood regression was also could not handle the overdispersion, but Quasi-Likelihood regression can improve the value of the standard error becomes greater than the value of the standard error on Poisson regression. Thus, by using the Quasi-Likelihood regression obtained three independent variables that affect the number of divorce cases in each urban city of Denpasar in 2011.
Co-Authors I KOMANG GDE SUKARSA I Putu Eka Nila Kencana