S
Samuel Iddi
Researcher at University of Ghana
Publications - 54
Citations - 566
Samuel Iddi is an academic researcher from University of Ghana. The author has contributed to research in topics: Overdispersion & Medicine. The author has an hindex of 12, co-authored 44 publications receiving 358 citations. Previous affiliations of Samuel Iddi include Katholieke Universiteit Leuven & University of Southern California.
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Journal Article
Statistical model for overdispersed count outcome with many zeros : an approach for marginal inference
TL;DR: In this paper, the authors developed a marginalised model for zero-inflated univariate count outcome in the presence of overdispersion, and implemented it using the SAS NLMIXED procedure with minimal coding efforts.
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Evaluation of the DWT-PCA/SVD Recognition Algorithm on Reconstructed Frontal Face Images
TL;DR: It was evident from the statistical assessment that the DWT-PCA/SVD algorithm gives relatively lower average recognition distance for the left reconstructed face images, and is recommended as a suitable algorithm for recognizing face images under partial occlusion (half face images).
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Respiratory and non-respiratory symptoms associated with pesticide management practices among farmers in Ghana's most important vegetable hub.
Reginald Quansah,John R. Bend,Frederick Ato Armah,Felix Bonney,Joshua Aseidu,David O. Yawson,Michael Osei Adu,Isaac Luginaah,David Kofi Essumang,Abukari Abdul-Rahaman,Samuel Jerry Cobbina,Samuel Iddi,Matthew Tersigni,Samuel Afful,Peter Osei-Fosu,Edward Nketiah-Amponsah +15 more
TL;DR: In spite of the fact that farmers have adequate knowledge about the environment and health effects of pesticides, several unhygienic practices are in widespread use, indicating that knowledge is not necessarily always translated in action.
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A Marginalized Combined Gamma Frailty and Normal Random-effects Model for Repeated, Overdispersed, Time-to-event Outcomes
TL;DR: In this paper, the authors proposed a marginalized model for repeated or otherwise hierarchical, overdispersed time-to-event outcomes, adapting the so-called combined model of Molenberghs et al. (in press), who combined gamma and normal random effects.
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Associated factors of pregnancy loss in two urban slums of Nairobi: A generalized estimation equations approach
TL;DR: In this article, the authors used the generalized estimation equation (GEE) to estimate pregnancy loss and identify associated factors that drive pregnancy loss among women in two urban slums in Nairobi.