Xplore: Journal of Statistics
Vol. 8 No. 1 (2019): 30 April 2019

Pemodelan Data Multi-Label dengan Pendekatan Multivariate Generalized Linear Mixed Model (MGLMM)

Dairul Fuhron (IPB)
. Indahwati (Department of Statistics, IPB University)
Farit Mochamad Afendi (Department of Statistics, IPB University)



Article Info

Publish Date
06 Apr 2019

Abstract

Multi-label data refers to a type of categorical data where an object may has more than one corresponding label or possible values. Multi-label data are commonly found in many fields, one of them is market research of the sweetened condensed milk (SCM) and sweetened condensed creamer (SCC) products. According to product characteristic, market research for the aforementioned product is appropriately conducted on the outlet level. An outlet may use more than one product’s brand in the same time frame. That condition inflict brand choice information to be represented under multi-label data. This research used problem transformation method by tranforming a multi-label variable into several single-label variables. Multivariate Generalized Linear Mixed Modeling or MGLMM was selected under consideration of binary multiple responses and correlated responses presumption. Five responses of SCM and SCC brand choice modeling resulted correct model without overdispersion and the scaled pearson chi square statistic is 0.99. Tests of fixed effects indicate three factor significantly affect SCM and SCC brand choice at the 5% level. They are purchase total, province, and type of business. The variance of the random effect intercept is 1.53×10−18 or insignificant, hence MGLMM based model was similar compare to separated GLM based model.

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Journal Info

Abbrev

xplore

Publisher

Subject

Decision Sciences, Operations Research & Management Engineering Mathematics

Description

Xplore: Journal of Statistics diterbitkan berkala 3 (tiga) kali dalam setahun yang memuat tulisan ilmiah yang berhubungan dengan bidang statistika. Artikel yang dimuat berupa hasil penelitian atau kajian pustaka dalam bidang statistika dan atau penerapannya. ISSN: 2302-5751 Mulai Desember 2018, ...