Open AccessMeta-Analysis of Fixed, Random and Mixed Effects Models
Author(s) -
Savita Jain,
Suresh Sharma,
Kanchan Jain
Publication year - 2019
Publication title -
international journal of mathematical, engineering and management sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.228
H-Index - 10
ISSN - 2455-7749
DOI - 10.33889/ijmems.2019.4.1-018
Subject(s) - random effects model , fixed effects model , funnel plot , meta analysis , macular degeneration , random forest , statistics , mixed model , population , medicine , mathematics , computer science , artificial intelligence , publication bias , ophthalmology , panel data , environmental health
A statistical procedure used for integrating the results obtained from a number of findings is termed as Meta-analysis. In a systematic review, all the information collected can be best used by increasing the power of analysis. The precision of treatment effects can be improved and accessed by statistically combining the results of similar studies. A very common degenerative disease among the elderly population with multiple genetic and environmental factors is Age-Related Macular Degeneration (AMD) that leads to the distorted central vision and severe visual loss in the early and advanced stage, respectively. In this study, the data sets from the results of 20 studies on the effectiveness of the treatments against AMD disease were analysed using fixed, random and mixed effect models. Various plots Forest, Funnel, Radial, QQ were also fitted for fixed, random and mixed effects models.