Abstract
Discrete ordinal response variables often exhibit an “excess” of zeros, which can be attributed to two different data conditions. Conventional ordinal probit models are limited in their ability to explain these excess zeros. The Zero Inflated Ordered Probit (ZIOP) model, which combines binary probit and ordinal probit regression, can be used to address this limitation. This study reviews the empirical analysis of the factors that contribute to poor household levels in East Kalimantan. The goodness-of-fit of the ZIOP and ordinal probit models was assessed using the Vuong test.
Original language | English |
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Pages (from-to) | 278-285 |
Number of pages | 8 |
Journal | Procedia Computer Science |
Volume | 234 |
DOIs | |
Publication status | Published - 2024 |
Event | 7th Information Systems International Conference, ISICO 2023 - Washington, United States Duration: 26 Jul 2023 → 28 Jul 2023 |
Keywords
- Marginal Effect
- Poor Household Rate
- Vuong Test
- Zero Inflated Ordered Probit (ZIOP)