✦ LIBER ✦

A Logistic Normal Multinomial Regression Model for Microbiome Compositional Data Analysis

✍ Scribed by Xia, Fan; Chen, Jun; Fung, Wing Kam; Li, Hongzhe

Book ID: 121691811
Publisher: John Wiley and Sons
Year: 2013
Tongue: English
Weight: 368 KB
Volume: 69
Category: Article
ISSN: 0006-341X
DOI: 10.1111/biom.12079

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

A multinomial logistic regression modeli

A multinomial logistic regression modeling approach for anomaly intrusion detection

✍ Yun Wang 📂 Article 📅 2005 🏛 Elsevier Science 🌐 English ⚖ 281 KB

Nonuniform DIF Detection using Discrimin

Nonuniform DIF Detection using Discriminant Logistic Analysis and Multinomial Logistic Regression: A comparison for polytomous items

✍ M. Dolores Hidalgo; Juana Gómez 📂 Article 📅 2006 🏛 Springer Netherlands 🌐 English ⚖ 136 KB

A hierarchical model for compositional d

A hierarchical model for compositional data analysis

✍ Mark J. Brewer; João A. N. Filipe; David A. Elston; Lorna A. Dawson; Robert W. M 📂 Article 📅 2005 🏛 Springer-Verlag 🌐 English ⚖ 347 KB

Statistical analysis of a combination of

Statistical analysis of a combination of objective and subjective environmental noise data using factor analysis and multinomial logistic regression

✍ Engel, Margret Sibylle; Vasconcelos Segundo, Emerson Hochsteiner; Zannin, Paulo 📂 Article 📅 2013 🏛 Springer 🌐 English ⚖ 334 KB

Analysis of vesicular-arbuscular mycorrh

Analysis of vesicular-arbuscular mycorrhizal colonization data with a logistic regression model

✍ Sonia A. Alvarez-Santiago; F. García-Oliva; Lucía Varela 📂 Article 📅 1996 🏛 Springer-Verlag 🌐 English ⚖ 219 KB

A discrete time logistic regression mode

A discrete time logistic regression model for analyzing censored survival data

✍ A. Maul 📂 Article 📅 1994 🏛 John Wiley and Sons 🌐 English ⚖ 676 KB

## SUM MARY Consideration is given to survival data analysis by modelling the hazard as a discrete function of time. This is done for each individual who is examined independently from the other individuals of the sample observed. Assuming time has been divided into intervals of the same length, t