Comparing two approaches for meta-analysis of binary outcomes

YOGESH C BANGAR; MED RAM VERMA

doi:10.56093/ijans.v90i2.98823

Authors

YOGESH C BANGAR Scientist, Department of Animal Genetics and Breeding, Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar, Haryana
MED RAM VERMA Principal Scientist, Division of Livestock Economics, Statistics and Information Technology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, Uttar Pradesh.

https://doi.org/10.56093/ijans.v90i2.98823

Keywords:

Bootstrap, Clinical mastitis, Dairy cows, Meta-analysis Present address, 1Scientist (yogeshbangar07@gmail.com), Department of

Abstract

In the present study, meta-analysis of binary outcome was undertaken by using two approaches namely Summary Statistics (SS) and Individual Animal Data (IAD) approach for obtaining more reliable estimates of the association of risk factors [breed (crossbred & indigenous), parity (primiparous & multiparous), age (< 5 years & > 5 years) and milk yield (kg)] with clinical mastitis [binary outcome (yes or No)] in dairy cows in India. For the present study the data on mastitis were compiled from three organized cattle farms. The results of bootstrapping showed that the pooled estimates under Individual Animal Data (IAD) approach were significantly higher than Summary Statistics (SS) appraoch for all unadjusted risk factors. However the results of both approaches were similar under covariate-adjusted circumstances. In case of heterogeneity of effects across farms, Individual Animal Data (IAD) approach provides more reliable information than Summary Statistics (SS) approach. Therfore it was also concluded that the crossbreds (adjusted for age) cows (1.47 times), older cows (1.85 times) multiparous cows (2.21 times) and high yielders (1.67 times) cows were at higher risk of mastitis than their respective reference categories. Therefore Individual Animal Data (IAD) approach is an appropriate approach for animal science data as it is more reliable and perform better in heterogenous conditions.

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