META-REGRESSION ANALYSIS OF RANDOMIZED CONTROLLED TRIALS OF THE RISK FACTORS OF SICKLE CELL DISEASE
Abstract
Replications are important for science, both statistically and otherwise. A plethora of epidemiology studies that have been done shows that there are always variations, errors and inconclusive findings in sickle cell disease. This paper intends to compute the underlying risk factor in sickle cell disease using meta-regression. These efficacy scores are retrieved from 19 studies. The effect size index was risk ratio and date were sourced via Pubmed, Science Direct, Web of Science, Medline, Rechargegate and Google scholar. The random-effect model was employed for the analysis. The studies in the analysis were assumed to be random samples from a vast number universe of sickle cell disease studies. The summary effect size was 1.84, with (95% CI: 1.567 - 2.148). The Z-value tested the null hypothesis that the summary effect size is 1. We found Z = 7.540 with p < 0.001 for α = 0.05; hence, we reject the null hypothesis and concluded that the summary effect size is not precisely 1. This study shows that the 3 moderators sighted are not responsible for the risk factors of sickle cell disease with p > 0.05. The Begg and Mazumdar rank correlation test, egger test, and funnel plot were used to determine publication bias across studies. To evaluate heterogeneity I2statistic and tau-squared were used
Keywords:
Meta-Regression, Random-effect, Risk Ratio, Egger Test, Risk Factor, Sickle Cell.Downloads
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https://doi.org/10.5281/zenodo.14745030Issue
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Copyright (c) 2025 Adehi M.U, Omole O.O, Bilkisu M, Adenomon M.O, Audi N.I
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