Alfred Adewole Abiodun
@unilorin.edu.ng
Associate Professor, Faculty of Physical Sciences
University of Ilorin
RESEARCH, TEACHING, or OTHER INTERESTS
Statistics and Probability
Scopus Publications
Scopus Publications
Eunice Job and Alfred Abiodun
IEEE
Proportional hazards (PH) model is one of the most commonly used methods in the analysis of time-to-event data. The assumption of (PH) model which states that the ratio of the hazards for any two individuals is constant over time may not hold if the hazard ratio varies with time. It is therefore necessary to use methods that do not assume proportionality to investigate the effects of covariates on survival time which leads us to non-proportional hazard (NPH) model. The PH model under frailty setting is a natural extension of the standard PH model to address the erroneous assumption that the baseline survival times are independently and identically distributed.This study compared non-proportional hazard (NPH) model without frailty and with frailty using Integrated Nested Laplace Approximation (INLA) method under the mixture of Weibull-Weibull, Lognormal-Lognormal and Weibull-Lognormal baseline distributions. Data were simulated from mixture of Weibull-Weibull, Lognormal-Lognormal and Weibull-Lognormal baseline hazard distributions for different sample sizes and censoring percentages. The NPH model without frailty and with frailty were then fitted to the data using Deviance Information Criterion (DIC) as the comparing metric.It was observed that the NPH model with frailty performed better than the NPH model without frailty in the three mixture of baseline distribution considered and also for all sample sizes and censoring percentages considered.
A. I. Ishaq, A. A. Abiodun, A. A. Suleiman, A. Usman, A. S. Mohammed, and M. Tasiu
IEEE
In developing nations like Nigeria, inflation impacts practically every aspect of the economy, and the expenses associated with it are substantial. The severity of the effects of inflation is determined by whether it was expected or unexpected. An expected inflation occurs when households and businesses can consistently forecast the future inflation rate at all times. However, unexpected inflation occurs when they are unable to estimate the future inflation rate. These measures are classified as monetary policy and fiscal policy. The use of statistical models in modelling and forecasting inflation is one of the most recent developments in economic and financial studies. In this study, a new continuous probability distribution is introduced that can be employed to model Nigerias inflation rate from January 2003 to June 2023. The distribution was developed by transforming the chi-square distribution with an additional parameter to unveil the inverse power chi-square distribution. The proposed model has a right and left-skewed form with increasing, constant, and decreasing failure rates, as can be seen from the density shapes. Some statistical properties and parameters of its estimates are examined. It was established that the suggested distribution was the most effective distribution for modeling Nigerias inflation rate.
Alfred Adewole Abiodun and Aliyu Ismail Ishaq
Informa UK Limited
Abstract The development of new generalizations based on certain baseline probability distribution has become one of the current trends in distribution theory literature. New generators are often required to define wider distributions for modelling real life data. In this study, we proposed and studied a new generalization of Maxwell and Lomax distributions using the T-X method. Several structural and statistical properties of the proposed distribution were obtained such as moments, quantile function, survival and hazard functions, skewness, kurtosis and order statistics. The method of maximum likelihood estimation (MLE) was used to estimate the parameters of the proposed distribution. In addition, a simulation study was conducted to evaluate the performance of the MLE method. The proposed distribution was applied to two real life datasets to illustrate its flexibility. It was found that the proposed distribution was superior to offer a better fit than the other competing extensions of Lomax distributions considered in the study.
Aliyu Ismail Ishaq, Alfred Adewole Abiodun, and Jamilu Yunusa Falgore
Elsevier BV
A. I. Ishaq, A. A. Abiodun, and U. Panitanarak
IEEE
In this study, a new statistical distribution, namely, the Maxwell-Exponentiated exponential distribution is developed in the application to financial data. This distribution serves as an alternative to Burr X-Exponentiated exponential, MarshallOlkin-Exponentiated Exponential and Type II Half Logistic-Exponentiated Exponential distributions. The quantile function of the proposed distribution was obtained. Some statistical properties and estimates of their parameters were studied. The performance of proposed distribution was carried out by using application to the data set relating to monthly Nigerian naira to CFA Franc exchange rate. The results showed that the proposed Maxwell-Exponentiated exponential distribution was chosen as the best fitted monthly Nigerian naira to CFA Franc exchange rate data by having a minimum values of AIC and CAIC.
Aliyu Ismail Ishaq and Alfred Adewole Abiodun
Springer Science and Business Media LLC
A. I. Ishaq and A. A. Abiodun
IEEE
In statistics and financial modeling, the Dagum model can be an alternative to log-nornal and pareto distributions in the applications of personal income, financial and wealth data, among others. This study proposed an extension of the Dagum model by adding an extra parameter from the Maxwell generalized family of distributions. Some properties of the extended Dagum model were studied. We illustrated the usefulness of the proposed distribution by applying two financial data related to Nigerian naira to Japanese Yen selling exchange rate data and the inflation rate of the United State of American data. It shown that, the Maxwell-Dagum model could be employed in modeling financial data apart from Weibul-Dagum, Topp-Leone-Dagum, Gamma-Dagum and Odd Log-Logistic-Dagum models.
K.A. Adeleke and A.A. Abiodun
Lifescience Global
Often in epidemiological research, introducing a stratified Cox model can account for the existence of interactions of some inherent factors with some major/noticeable factors. This paper aims at modelling correlated variables in infant mortality with the existence of some inherent factors affecting the infant survival function. A Stratified Cox model is proposed with a view to taking care of multi-factor-level that has interactions with others. This, however, is used as a tool to model infant mortality data from Nigeria Demographic and Health Survey (NDHS) with g-level-factor (Tetanus, Polio and Breastfeeding) having correlations with main factors (Sex, infant Size and Mode of Delivery). Asymptotic properties of partial likelihood estimators of regression parameters are also studied via simulation. The proposed models are tested via data and it shows good fit and performs differently depending on the levels of the interaction of the strata variable Z*. An evidence that the baseline hazard functions and regression coefficients are not the same from stratum to stratum provides a gain in information as against the usage of the Cox model. Simulation result shows that the present method produces better estimates in terms of bias, lower standard errors, and or mean square errors.
Kazeem A. Adeleke, Alfred A Abiodun, and R. A. Ipinyomi
Wayne State University Library System
The application of survival analysis has extended the importance of statistical methods for time to event data that incorporate time dependent covariates. The Cox proportional hazards model is one such method that is widely used. An extension of the Cox model with time-dependent covariates was adopted when proportionality assumption are violated. The purpose of this study is to validate the model assumption when hazard rate varies with time. This approach is applied to model data on duration of infertility subject to time varying covariate. Validity is assessed by a set of simulation experiments and results indicate that a non proportional hazard model performs well in the phase of violated assumptions of the Cox proportional hazards.
Alfred A. Abiodun, Samson Babatunde Adebayo, Benjamin A. Oyejola, and Jennifer Anyanti
Springer Netherlands
EmmanuelO Sanya, Philip Kolo, Kehinde Adekeye, AlfredA Abiodun, and TimothyO Olanrewaju
Medknow
BACKGROUND
Old age is one of the factors associated with increased risk of dying when admitted to hospital. Therefore, aim of this study was to examine causes and pattern of death among elderly patients managed in a tertiary care hospital in Nigeria with scanty mortality records.
MATERIALS AND METHODS
This prospective study was on deaths that occurred in patients 60 years and above admitted to University of Ilorin Teaching Hospital (UITH), Ilorin, between January 2005 and June 2007. Excluded were all brought-in-dead during the study period. Information obtained included demographic data, duration on admission, and diagnosis. Causes of death were determined from clinical progress notes and diagnosis.
RESULTS
A total of 1298 deaths occurred during the study period, of which 297 occurred in persons 60 years and above with crude death rate of 22.8%. The mean age at death was 68 ± 9 years (ranged 60-100 years). This consisted of 59% males and 41% females. Mean age at death for females was 69.7 ± 8.7 years and for males 68.1 ± 9.8 years (P = 0.05). Mean values of serum chemistry were sodium 137 ± 8 mMol/l, potassium 3.6 ± 1 mMol/l, urea 11 ± 8 mMol/l, and creatinine 126 ± 91 μmol/l. The value of mean haemogram concentration was 10.5 ± 3 gm/dl and white cell count was 12 ± 2 × 10(9)/mm3. The three most common diagnoses at deaths were stroke (19.8%), sepsis (16.5%), and lower respiratory tract disease (8.1%). Infectious diseases accounted for 38.2% of all diagnoses. Collective mean length of hospital stay (LOS) at death was 6.8 ± 8.6 (ranged 15 minutes-60 days). Close to 27.4% of the deaths occurred within 24 hours and neurological disorder had shortest hospital stay (4.6 ± 6.3 days), followed by endocrine disorders (6.8 ± 8.4 days) and respiratory diseases (8.4 ± 5.6 days) [P = 0.001].
CONCLUSION
Hospital mortality is high amongst older people. Stroke and infectious diseases are leading causes of death. Efforts should be geared toward reducing risk for cardiovascular diseases and improvement on level of personal and community hygiene.