How to do meta-analysis correctly?
Introduction
In order for the publication of the article and any other scientific work to take place, as well as to be worthy of recognition by others, all the data collected and the results obtained must lend themselves to a holistic analysis and systematization. Structure and clarity are the main requirements of Scopus, BAK, WoS articles. A meta-analysis is performed for the greatest concentration of professional effectiveness of the study. This is a complete statistical analysis of the results and their heterogeneity, which identifies, examines and explains the initial heterogeneity and difference in the results of the study. Statistical calculations increase the feasibility and objectivity of valid conclusions. Any topics of scientific articles require qualitative statistical data, in their achievement help various methods, consisting of processing criteria, statistics of the available heterogeneity in the results, obtaining a generalized estimate of the effect size, the sensitivity analysis of the conclusions.
Variations in meta-analysis methods
The methods differ from the main approaches in the narrow focus of specialization. First of all, the statistical approach depends on the type of data being analyzed and their effects.
Binary data - calculating odds ratios, relative (or different) risk versus samples.
Continuous data - range of values of the studied object behavior.
For studies with internal dispersion is used Mantel-Hansel method.
To calculate the OWL:
For the criterion of checking the significance of the overall measure of connectivity:
For statistics:
For research with random effects the variance is summed up both within and between trials.
Cumulative meta-analysis - calculation of a priori and posteriori probabilities.
Bayesian meta-analysis - calculation of a priori probabilities of effectiveness of interventions, taking into account indirect data.
Regression meta-analysis - consideration of the influence of several characteristics of the study on its results.
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