USE of group sequential test methods in the survival analysis in aquaculture
Yazarlar (3)
Dr. Öğr. Üyesi Zeynep GÖKKUŞ Kastamonu Üniversitesi, Türkiye
Prof. Dr. Kamil Alakuş Ondokuz Mayıs Üniversitesi, Türkiye
Doç. Dr. Soner BİLEN Kastamonu Üniversitesi, Türkiye
Makale Türü Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
Dergi Adı Aquaculture (Q1)
Dergi ISSN 0044-8486 Wos Dergi Scopus Dergi
Dergi Tarandığı Indeksler SCI-Expanded
Makale Dili İngilizce Basım Tarihi 01-2020
Kabul Tarihi Yayınlanma Tarihi 01-01-2020
Cilt / Sayı / Sayfa 515 / 1 / 734568–0 DOI 10.1016/j.aquaculture.2019.734568
Makale Linki https://www.sciencedirect.com/science/article/abs/pii/S0044848618320908?casa_token=P7uqRnaZ-gAAAAAA:S_oedgBfxbViynvTpyX7mLTsu6xYYqEgLH438_fpAwEAeYSIunXic_2HwUZDfPQox330Kwv7APg
UAK Araştırma Alanları
Su Ürünleri Yetiştiriciliği
Özet
The information obtained as a result of research in natural sciences should have a high statistical power, that is also valid for the field of aquaculture. The sample size needs to be increased in order to increase the statistical power of a scientific study. However, studying on large sample size may not always be possible. Therefore, many experimental designs have been developed for data collection purposes to keep the sample size minimum. Group sequential designs have been enhanced for the data entered sequentially to the trial most of the time in medicine, production, economy etc. With these designs, the studies can be early terminated and results can also be obtained the results based on with high statistical power with smaller sample size. These experimental designs are specifically applied to survival data. In the survival analysis used in the field of aquaculture, all of the samples are included at the …
Anahtar Kelimeler
Group sequential test methods | Power analysis | Sample size | Survival analysis | Trial design in aquaculture
Science Direct
BM Sürdürülebilir Kalkınma Amaçları
Atıf Sayıları
Scopus 1
Google Scholar 2
USE of group sequential test methods in the survival analysis in aquaculture

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