A New Measure for an Acceptable Level of Homogeneity in Meta-Informatics DOI Creative Commons
Ramalingam Shanmugam, Karan P. Singh

Mathematics, Год журнала: 2025, Номер 13(9), С. 1364 - 1364

Опубликована: Апрель 22, 2025

This paper addresses the challenges in assessing heterogeneity meta-analytic studies. The specifics include mental health research work. Three key statistical scores meta-analytics—Higgins’ I2, Birge’s H2, and newly developed S2 score—are discussed illustrated. critiques subjectivity of these introduces elasticity to enhance accuracy objectivity heterogeneity. integration into meta-informatic score measures how changes as new studies are added, improving interpretation results. Also, authors compute compare context research, offering a novel approach visualizing quantifying demonstrate improves assessment recommends use score, integrated with elasticity, for more reliable objective conclusions well other meta-analyses. rectified S2, overcomes issues I2 when chi-squared distribution fails due small sample sizes or negative values.

Язык: Английский

A New Measure for an Acceptable Level of Homogeneity in Meta-Informatics DOI Creative Commons
Ramalingam Shanmugam, Karan P. Singh

Mathematics, Год журнала: 2025, Номер 13(9), С. 1364 - 1364

Опубликована: Апрель 22, 2025

This paper addresses the challenges in assessing heterogeneity meta-analytic studies. The specifics include mental health research work. Three key statistical scores meta-analytics—Higgins’ I2, Birge’s H2, and newly developed S2 score—are discussed illustrated. critiques subjectivity of these introduces elasticity to enhance accuracy objectivity heterogeneity. integration into meta-informatic score measures how changes as new studies are added, improving interpretation results. Also, authors compute compare context research, offering a novel approach visualizing quantifying demonstrate improves assessment recommends use score, integrated with elasticity, for more reliable objective conclusions well other meta-analyses. rectified S2, overcomes issues I2 when chi-squared distribution fails due small sample sizes or negative values.

Язык: Английский

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