ORCID Profile
0000-0002-9723-0448
Current Organisations
Quaid-i-Azam University
,
University of New South Wales
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Publisher: Wiley
Date: 25-06-2018
DOI: 10.1002/SIM.7850
Abstract: Regression to the mean (RTM) can occur whenever an extreme observation is selected from a population and a later observation is closer to the population mean. A consequence of this phenomenon is that natural variability can be mistaken as real change. Simple expressions are available to quantify RTM when the underlying distribution is bivariate normal. However, there are many real-world situations, which are better approximated as a Poisson process. Ex les include the number of hard disk failures during a year, the number of cargo ships damaged by waves, daily homicide counts in California, and the number of deaths per quarter attributable to acquired immune deficiency syndrome in Australia. In this paper, we derive expressions for quantifying RTM effects for the bivariate Poisson distribution for both the homogeneous and inhomogeneous cases. Statistical properties of our derivations have been evaluated through a simulation study. The asymptotic distributions of RTM estimators have been derived. The RTM effect for the number of people killed in road accidents in different regions of New South Wales (Australia) is estimated using maximum likelihood.
Publisher: Wiley
Date: 11-02-2019
DOI: 10.1002/SIM.8115
Abstract: Regression to the mean (RTM) occurs when subjects having relatively high or low measurements are remeasured and found closer to the population mean. This phenomenon can potentially lead to an inaccurate conclusion in a pre-post study design. Expressions are available for quantifying RTM when the distribution of pre and post observations are bivariate normal and bivariate Poisson. However, situations exist where the response variables are the number of successes in a fixed number of trials and follow the bivariate binomial distribution. In this article, expressions for quantifying RTM effects are derived when the underlying distribution is the bivariate binomial. Unlike the normal and Poisson distributions, the correlation between pre and post observations can be either negative or positive under the bivariate binomial distribution and the severity of RTM is greater in the former case. The percentage relative difference is used to highlight the differences in quantifying RTM under the bivariate binomial distribution and normal and Poisson approximations to the bivariate binomial distribution. Expressions for estimating RTM using the method of maximum likelihood along with its asymptotic distribution are derived. A simulation study is conducted to empirically assess the statistical properties of the RTM estimator and its asymptotic distribution. Data ex les using the number of obese in iduals and the number of nonconforming cardboard cans are discussed.
Publisher: Informa UK Limited
Date: 14-02-2023
Publisher: MDPI AG
Date: 11-12-2022
DOI: 10.3390/TROPICALMED7120430
Abstract: Toxoplasmosis is a zoonotic parasitic disease caused by T. gondii, an obligate intracellular apcomplexan zoonotic parasite that is geographically worldwide in distribution. The parasite infects humans and all warm-blooded animals and is highly prevalent in various geographical regions of the world, including Pakistan. The current study addressee prevalence of Toxoplasma infection in women in various geographical regions, mapping of endemic ision and t district of Khyber Pakhtunkhwa province through geographical information system (GIS) in order to locate endemic regions, monitor seasonal and annual increase in prevalence of infection in women patients. Setting: Tertiary hospitals and basic health care centers located in 7 isions and 24 districts of Khyber Pakhtunkhwa (KP) province of Pakistan. During the current study, 3586 women patients from 7 isions and 24 districts were clinically examined and screened for prevalence of T. gondii infection. Participants were screened for Toxoplasma infection using ICT and latex agglutination test (LAT) as initial screening assay, while iELISA (IgM, IgG) was used as confirmatory assay. Mapping of the studied region was developed by using ArcGIS 10.5. Spatial analyst tools were applied by using Kriging/Co-kriging techniques, followed by IDW (Inverse Distance Weight) techniques. Overall prevalence of T. gondii infection was found in 881 (24.56%) patients. A significant ( .05) variation was found in prevalence of infection in different isions and districts of the province. Prevalence of infection was significantly ( .05) high 129 (30.07%) in Kohat Division, followed by 177 (29.06%), 80 (27.87%), 287 (26.72%), 81 (21.21%), 47 (21.07%), and 80 (13.71%) cases in Hazara Division, D.I Khan Division, Malakand Division, Mardan Division, Bannu Division, and Peshawar Division. Among various districts, a significant variation ( .05) was found in prevalence of infection. Prevalence of infection was significantly ( .05) high 49 (44.95%) in district Karak, while low (16 (10.81%) in district Nowshera. No significant ( .05) seasonal and annual variation was found in prevalence of Toxoplasma infection. LAT, ICT and ELISA assays were evaluated for prevalence of infection, which significantly ( .05) detected T. gondii antibodies. LAT, ICT and ELISA assays significantly ( .05) detected infection, while no significant ( .05) difference was found between positivity of LAT and ICT assays. A significant difference ( .05) was found in positivity of Toxoplasma-specific (IgM), (IgG) and (IgM, IgG) immunoglobulin by ICT and ELISA assay. The current study provides comprehensive information about geographical distribution, seasonal and annual variation of Toxoplasmosis infection in various regions of Khyber Pakhtunkhwa province of Pakistan. Infection of T. gondii in women shows an alarming situation of disease transmission from infected animals in the studied region, which is not only a serious and potential threat for adverse pregnancy outcomes, but also cause socioeconomic burden and challenges for various public and animal health organizations in Pakistan and across the country.
No related grants have been discovered for Manzoor Khan.