A5025661821- Statistical Methods and Bayesian Inference
- Statistical Methods and Inference
- Advanced Causal Inference Techniques
- Bayesian Methods and Mixture Models
- Autoimmune and Inflammatory Disorders Research
- Optimal Experimental Design Methods
- COVID-19 Clinical Research Studies
- Bayesian Modeling and Causal Inference
- Statistical Methods in Clinical Trials
- Pharmaceutical Quality and Counterfeiting
- Flavonoids in Medical Research
- Pain Mechanisms and Treatments
- Geophysical and Geoelectrical Methods
- Advanced Multi-Objective Optimization Algorithms
- COVID-19 and Mental Health
- Drug-Induced Adverse Reactions
- Epigenetics and DNA Methylation
- Electrical and Bioimpedance Tomography
- Diabetic Foot Ulcer Assessment and Management
- Groundwater flow and contamination studies
- Cancer, Hypoxia, and Metabolism
- Antibiotic Use and Resistance
- Cancer Cells and Metastasis
- Census and Population Estimation
King Saud University
2010-2024
In the vast statistical literature, there are numerous probability distribution models that can model data from real-world phenomena. New models, nevertheless, still required in order to represent with various spread behaviors. It is a known fact great need for new limited support. this study, flexible called unit Maxwell-Boltzmann distribution, which values interval, derived by selecting as base-line model. The important characteristics of terms statistics and mathematics investigated...
Abstract Aim The dynamics of coronavirus disease 2019 (COVID‐19) pandemic has become special concern to the rheumatology community. Rheumatic patients are required engage in effective health management but their behavior is often influenced by intrinsic and extrinsic factors. This cross‐sectional study aims examine patients’ experiences during current its implication on perception behavior. Method A patient‐centered electronic survey was used, randomly sampling rheumatic Saudi Arabia March...
Count data consists of both observed and unobserved events. The analysis count often encounters overdispersion, where traditional Poisson models may not be adequate. In this paper, we introduce a tractable one-parameter mixed distribution, which combines the distribution with improved second-degree Lindley distribution. This called Poisson-improved is capable effectively modeling standard overdispersion. However, if frequency events unknown, proposed cannot directly used to describe To...
The purpose of this paper is to classify UIS data in order identify their risk, reduce drug abuse, and prevent high-risk HIV behavior. A method for fitting proportional hazards models censored survival described. Stratification performed recursively. tree-based developed, based on maximizing the difference between groups patients represented by nodes a binary tree.
Antimicrobial dispensing without a prescription has been identified as significant contributor to the burgeoning crisis of antimicrobial resistance. To combat this, Saudi Ministry Health introduced stringent restriction policy in mid-2018, mandating prescriptions for all drug dispensations at pharmacies. Therefore, this study aimed assess immediate impact on retail sales. do so, we analyzed annual sales data from 2017 2019 sourced IQVIA-MIDAS® database, which included range antimicrobials,...
Background and Aim: Diabetic neuropathy is the commonest early long-term complication of diabetes. Saudi Arabia has a high prevalence diabetic reaching (65%), which necessitate establishment preventive program. The aim study was to measure its associated risk factors in Qassim, Arabia. Methods: A cross-sectional that utilized an adopted translated version Michigan screening instrument. An electronic questionnaire filled by each participant after obtaining inform consent. included...
We proposed three methods to find an approximate confidence interval for the variance of random effects a one-way analysis model in completely randomized design. compared with some other reported literature. Several criteria are used empirical comparisons: mean width interval, width, and coverage probability. use Simulation Monte-Carlo techniques perform comparison study. R language facilitate simulation procedures. found that one was general superior others.
In any longitudinal study, a dropout before the final timepoint can rarely be avoided. The chosen model is commonly one of these types: Missing Completely at Random (MCAR), (MAR), Not (MNAR), and Shared Parameter (SP). this paper we estimate parameters for simulated data real using Linear Mixed Effect (LME) method. We investigate consequences misspecifying missingness mechanism by deriving so-called least false values. These are values parameter estimates converge to, when assumptions may...