𝔖 Scriptorium
✦   LIBER   ✦

πŸ“

Hierarchical Linear Models: Applications and Data Analysis Methods

✍ Scribed by Stephen W. Raudenbush, Anthony S. Bryk


Publisher
SAGE Publications
Year
2002
Tongue
English
Leaves
510
Series
Advanced Quantitative Techniques in the Social Sciences 1
Edition
2nd
Category
Library

⬇  Acquire This Volume

No coin nor oath required. For personal study only.

✦ Subjects


ΠŸΡ€ΠΈΠΊΠ»Π°Π΄Π½Π°Ρ матСматичСская статистика


πŸ“œ SIMILAR VOLUMES


Hierarchical Linear Models: Applications
✍ Raudenbush, Stephen W.; Bryk, Anthony S. πŸ“‚ Library πŸ“… 2002 πŸ› Sage Publications 🌐 English

"This is a first-class book dealing with one of the most important areas of current research in applied statistics…the methods described are widely applicable…the standard of exposition is extremely high." --Short Book Reviews from the International Statistical Institute "The new chapters (10-14

Data analysis using hierarchical general
✍ Youngjo Lee, Lars Ronnegard, Maengseok Noh πŸ“‚ Library πŸ“… 2017 πŸ› Chapman and Hall/;CRC Press 🌐 English

<P>Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. Interest in the topic has grown, and various practical analytical tools have been developed. This book summarizes developments within the

Data analysis using hierarchical general
✍ Youngjo Lee, Lars Ronnegard, Maengseok Noh πŸ“‚ Library πŸ“… 2017 πŸ› Chapman and Hall/;CRC Press 🌐 English

<P>Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. Interest in the topic has grown, and various practical analytical tools have been developed. This book summarizes developments within the

Data Analysis Using Hierarchical General
✍ Youngjo Lee, Lars Ronnegard, Maengseok Noh πŸ“‚ Library πŸ“… 2017 πŸ› Chapman and Hall/CRC 🌐 English

<P>Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. Interest in the topic has grown, and various practical analytical tools have been developed. This book summarizes developments within the