classification
model based on the
logistic regression method has been proposed and developed. The developed
Timasheva, Yanina,
Kochetova, Olga,
Balkhiyarova, Zhanna,
Korytina, Gulnaz,
Prokopenko, Inga,
Nouwen, Arie (2025) variants across these pathways in 279 MetS patients and 397 healthy individuals. Using
logistic regression
Timasheva, Y.,
Balkhiyarova, Z.,
Avzaletdinova, D.,
Rassoleeva, I.,
Morugova, T.V.,
Korytina, G.,
Prokopenko, I.,
Kochetova, O. (2023) ability of the
model containing polygenic scores for the variants associated with T2D in our dataset
outcome were studied by binary
logistic regression. Results. Univariate analysis showed that the risk
Tao, Pan,
Galiullin, D,
Chen, X.L.,
Zhang, W.H.,
Yang, K,
Liu, K,
Zhao, L.Y.,
Chen, X.Z.,
Hu, J.K. (2021) . The performance of the
model was assessed with its discrimination, calibration, and clinical usefulness. A total
).
Logistic regression was used to detect the association of SNPs and haplotypes of linked loci in different
Timasheva, Y,
Nasibullin, TR,
Tuktarova, IA,
Erdman, VV,
Galiullin, TR,
Zaplakhova, OV,
Bakhtiiarova, KZ (2022) tested using
logistic regression analysis under additive genetic
model adjusted for sex. Meta