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Oludare Ariyo is a lecturer at the department of the Statistics Federal University of Agriculture, Abeokuta (FUNAAB). He received his PhD (Biostatistics) at the KU Leuven Belgium on Bayesian model selection for longitudinal random-effects models. He has gained expertise in various statistical topics with research interests, including Bayesian methods, longitudinal analysis, statistical modelling, missing data/ survival analysis, and mixed models / random-effects models / multilevel models. His research has led to several papers in highly qualified peer-reviewed international journals (citation statistics from: https://scholar.google.com/citations?hl=en&user=iicdhdYAAAAJ)
Before his appointment in FUNAAB, Dr Ariyo has worked as a Data Analyst at the Crop-Utilization Units, International Institutes of Tropical Agriculture (IITA), Ibadan, where he was involved in analysing all the data generated in the crop utilization laboratory using correct statistical tools. He later worked as a senior statistician at National Horticultural Research Institutes (NIHORT), Ibadan. There, he designs and handles statistical data analysis for scientists on a designed experiment. For over six years of working with these research institutes, Dr Ariyo had gain experience in applying Statistical methodology to real-life problems, especially in Agriculture. During his four and half years of stay at the Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-BioStat), Leuven, Belgium, Dr Ariyo further gained clinical trials experience and applied statistical methodology in medical studies.
Dr Ariyo has been involved in research collaboration with scientists within and outside Nigeria. Some of these collaborations have resulted in joint publications while others are either ongoing or under review: Prof E.C Merkle (Department of Psychometrics and Computing, University of Missouri, USA), Drs Lizbeth Naranjo (Department of Mathematics, Facultad de Ciencias, Universidad Nacional Autonoma de Mexico), Ricardo Ramirez-Aldana (Research Division, Instituto Nacional de Geriatria, Mexico), Adeleke Mathew (Discipline of Genetics, School of Life Sciences, University of Kwa-Zulu Natal, Westville, Durban 4001, South Africa), Takam Soh ( Département de Mathématiques, University of Yaounde I.), Leonard Nwoguikojo (Department of Statistics, University of Nigeria Nsukka) to name a few examples.
Dr Ariyo is an experienced R user with two R functions (https://github.com/OludareAriyo) currently working on an R package. Besides, he has an excellent working knowledge of the following software: SAS, JAGS, STAN, SPSS, Epi Info etc
He is a member of many professional bodies, has presented papers in international conferences across continents (recently he was invited as a spotlight speaker at the international meetings of Psychometric), and has received several grants. He is currently the coordinator of FUNAAB-LISA (FUNAAB-Laboratory for Interdisciplinary Statistical Analysis) and an advisor to Overleaf ( a collaborative cloud-based LaTeX editor used for writing, editing and publishing scientific documents.).
He is married with children.
(a) Doctor of Philosophy (PhD.) in Biostatistics 2020
(b) Master of Science, (M.Sc) in Statistics 2010
(c) Bachelor of Science (B.Sc) in Statistics 2005
(d) Senior Secondary School Certificate (SSCE) 1999
(i) Completed:
(a) A Spatio-temporal study of prevalence HIV in Mexico: analyses of descriptive Spatio-temporal features, risks’ tendencies and clustering by state.
(b) Bayesian modelling of autoregressive linear mixed models for longitudinal data.
(ii) In progress :
(a) Exploring posterior p-values for model assessment in longitudinal modelling.
(b) Exploring prior distributions for constrained correlation matrices.
(c) Analysis of longitudinal growth data: A Bayesian versus Frequentist approach.
• 2017:Travel Award to attend World Statistical Congress Marrakech Morroco by the World Bank Washington DC, USA.
• 2017: Travel Award to attend Conference of the International Society for Clinical Biostatistics Vigo, Spain, by International Biometric Society Washington DC, USA.
• 2015: Tertiary Education Trust Fund AST&D Grant for PhD in Biostatistics at Katholieke Universiteit by Federal Government of Nigeria through Federal University of Agriculture, Abeokuta.
• 2012: Travel Award to attend International Biometric Conference held in Kobe Japan by International Biometric Society Washington DC, USA.
• 2012: Second-runner up, Young-Statistician Show-case, organised by International Biometrics Society held in Kobe, Japan.
(i) Staff Adviser (FNG II) 2021–
(ii) Member, University SIWES Committee 2021-
(iii) Coordinator FUNAAB-LISA 2020 –
(iv) Level Coordinator, 100L (2014/2015 & 2015/2016) 2014 – 2016
(v) Assistant Undergraduate Results Officer 2014 – 2016
(vi) Statistical consultancy (KU, Leuven, Belgium) 2016 – 2020
(i) Member, Statistical Modelling Society.
(ii) Member, International Society for Clinical Biostatistics.
(iii) Member, International Statistical Institutes.
(iv) Member, Belgian Statistics Association.
(v) Member, International Biometrics Society.
(vi) Member, Nigeria Statistics Association
(a) Ariyo, O., Verbeke, G., and Lesaffre, E (2019): Bayesian model selection for generalised linear mixed model: Paper presentation at 40th Annual Conference of the International Society for Clinical Biostatistics held at Leuven Belgium 14-18, July 2019.
(b) Ariyo, O and Laseffre, E (2017). Bayesian Inference for skew-normal linear mixed models with covariates measurements errors. Paper presented at 38th Annual Conference of the International Society for Clinical Biostatistics held at Vigo Spain, 9-13, July 2017.
(c) Ariyo, O., Quintero, A ., Verbeke, G and Lesaffre, E (2017): Model selection for the skew-normal linear mixed models with covariate measurements errors: A Bayesian approach. Paper presented at 6th IBS Channel Network Conference held at the Hasselt Univesity, Diepenbeek, Belgium 24-26 April 2017.
(d) Ariyo, O and Laseffre, E (2017). Comparing skew-normal linear mixed models with nonignorable dropout via observed deviance information criterion. Paper presentation at 61st World Statistics Congress to hold at Marrakech, Morroco between July 16 and 21, 2017
(e) Ariyo, O., Yusuff, K and Wale-Orojo, O, (2015). Fitting the log-skew normal distribution to assess hypertensive patients’ atherosclerosis level in Irewole Local Government Area of Osun State Nigeria. 14th Bi-Annual conference of the Sub-Saharan African network (SUSAN) of International biometrics society (IBS) held at the University of Ibadan, Nigeria.
(f) Wale-Orojo O., Olayiwola O., Ariyo O. and Yusuff K. (2015): Efficiency of Stratified Diagonal Ranked Set Sampling for the Estimation of Unknown Population Parameter. International Biometric Society Sub-Sahara African Regional Scientific Conference 11th – 13th November 2015.
(g) Yusuff K. ., Bello R., Ariyo O. ., and Wale-Orojo O. (2015): A Reflection of Similarities between electrical Conductivity and Total Dissolved Soloids Quantities in Borehole Water from Fitted Optimisation Models. International Biometric Society Sub-Sahara African Regional Scientific Conference 11th – 13th November 2015.
(i) Dissertation/Thesis
(a) Ariyo, O.S (2005): Modeling Climatic Variation to Cocoa yields. A case of Cocoa Research Institutes of Nigeria Ibadan. A B.Sc Project University of Agriculture, Abeokuta, Nigeria.
(b) Ariyo, O.S (2010): Cost Sensitivity of Classical Classification Functions. M.Sc Dissertation. University of Agriculture, Abeokuta, Nigeria.
(c) Ariyo, O.S (2020): Bayesian model selection for longitudinal random-effects models. PhD Thesis Katholieke Universities, Leuven, Belgium
(ii) Journal Articles in Print
(1) Ariyo, O. and Adebanji, A. (2011): Robust Linear Classifier under unequal cost of misclassification. CBN Journal of Applied Statistics 2(1); 51-59. Published by Nigeria Statistical Association, NIGERIA.
(2) Ariyo, O., Akintunde, A., and AdeOluwa, O. (2015): Comparison of clustering methods for different data types using Rand index. Journal of Nigeria Statistical Association 27; 74-88, Published by Nigeria Statistical Association, NIGERIA.
(3) Ariyo, O., Adeleke, M., Yusuff, K. and Wale-Orojo, O. (2017): Comparison of non-linear mixed models fitted to longitudinal growths data of two breeds of chicken. FUNAI Journal of Science & Technology 1(1);101-108, Published by Federal University, Ndufu-Alike Ikwo (FUNAI), Nigeria, NIGERIA available online at www.fjst.org.
(4) * Dawodu, G., Akintunde, A. and Ariyo, O. (2017): Stochastic Prediction of Monthly Inflation Rates through Kalman Filtering. Journal of Natural Sciences, Engineering and Technology 16(2); 11-25. Published by Federal University of Agriculture, Abeokuta, NIGERIA and available online at https://journal.unaab.edu.ng/index.php/JNSET/article/view/1842.
(5) Ariyo, O., Quintero, A., Munoz, J., Verbeke, G., and Lesaffre, E. (2020): Bayesian model selection in the linear mixed model for longitudinal data. Journal of Applied Statistics 47(5); 890-913, Published by Taylor & Francis, CANADA available online at https://www.tandfonline.com/doi/full/10.1080/02664763.2019.1657814?journalCode=cjas20
(6) Ariyo, O., Lesaffre, E., Verbeke, G and Quintero, A (2019): Model selection for Bayesian linear mixed models with longitudinal data: Sensitivity to the choice of priors. Communications in Statistics-Simulation and Computation Published by Taylor & Francis, UK, Accepted date: 30th September 2019 and available online on 11th October 2019 at https://www.tandfonline.com/doi/citedby/10.1080/03610918.2019.1676439?scroll=top&needAccess=true
(7) Ariyo, O and Adeleke, M (2021): Simultaneous Bayesian modelling of skew-normal longitudinal measurements with non-ignorable dropout. Computational Statistics. Published by Springer, Germany. https://link.springer.com/article/10.1007/s00180-021-01118-y
(8) Ariyo, O., Lesaffre, E., Verbeke, G. and Quintero, A. (2021). Bayesian model selection for longitudinal count data, Sankhya B Published by Springer, Germany.
(9) Ariyo, O., Lesaffre, E., Verbeke, G., Huisman, M., Rijnhart, J., Heymans, M. and Twisk, J., (2021). Bayesian model selection for multilevel mediation models. Statistica Neerlandica. Published by Wiley, UK. Doi. 10.1111/stan.12256
(iii) Books: Nil
(iv) Technical Reports/Software Developed
(1) Ariyo, O., Quintero, A., and Munoz, J. (2019). Bayesselect: An R function that computes conditional and marginalised DIC, WAIC and PSBF for model selection for the linear mixed model with skew-normal random effects and measurement error for longitudinal data. https://ibiostat.be/online-resources/bayesian and https://github.com/OludareAriyo/Bayesselect
(2) Ariyo, O. (2019). BayesselectGLMM: An R function that computes conditional and marginalised DIC, WAIC and PSBF for model selection for generalised linear mixed model via replication and importance sampling
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