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r_workshop6 [2021/02/08 15:13]
egongora This workshop will now be Workshop 7 and will cover LMMs and GLMMs.
r_workshop6 [2021/03/23 12:35] (current)
lsherin
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 //The content of this workshop has been peer-reviewed by several QCBS members. If you would like to suggest modifications,​ please contact the current series coordinators,​ listed on the main wiki page// //The content of this workshop has been peer-reviewed by several QCBS members. If you would like to suggest modifications,​ please contact the current series coordinators,​ listed on the main wiki page//
  
-====== **NOTEWe have changed the structure and order of Workshops 6 and 7** ======+<wrap em>​IMPORTANT NOTICEMAJOR UPDATES</​wrap>​
  
-If you are looking for the workshop covering generalized linear models, please refer to **[[r_workshop7|Workshop 6]]**. 
  
-If you are looking for the workshop covering general and generalized linear mixed-effects models, please refer to **[[r_workshop6|Workshop 7]]**.+**March 2021 update:** This wiki has been discontinued and is no longer being actively developed or updated. Updated materials for the QCBS R Workshop Series are now housed on the QCBS R Workshop ​[[https://​github.com/​QCBSRworkshops/​workshop07|GitHub page]]. 
  
-====== Workshop 7: General ​and generalized linear mixed-effects ​models ======+Available materials include; 
 +  - The [[https://​qcbsrworkshops.github.io/​workshop07/​pres-en/​workshop07-pres-en.html|Rmarkdown presentation]] for this workshop; 
 +  - An [[https://​qcbsrworkshops.github.io/​workshop07/​book-en/​workshop07-script-en.R|R script]] that follows the presentation;​ 
 +  - [[https://​qcbsrworkshops.github.io/​workshop07/​book-en/​index.html|Written materials]] that accompany the presentation in bookdown format. 
 + 
 +**January 2021 update:** The structure of Workshops 6 + 7 have been changed.  
 + 
 +If you are looking for the workshop covering generalized linear models (GLM), please refer to [[r_workshop7|Workshop 6]]. 
 + 
 +If you are looking for the workshop covering linear and generalized linear mixed models (LMM and GLMM), please refer to [[r_workshop6|Workshop 7]]. 
 + 
 +====== Workshop 7: Linear ​and generalized linear mixed models ======
  
 Developed by: Catherine Baltazar, Dalal Hanna, Jacob Ziegler Developed by: Catherine Baltazar, Dalal Hanna, Jacob Ziegler
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 **Summary:​** Mixed effects models allow ecologists to overcome a number of limitations associated with traditional linear models. In this workshop, you will learn when it is important to use a mixed effects model to analyze your data. We will walk you through the steps to conduct a linear mixed model analysis, check its assumptions,​ report results, and visually represent your model in R. We will also build on the previous workshop to combine knowledge on linear mixed models and extend it to generalized linear mixed effect models. **Summary:​** Mixed effects models allow ecologists to overcome a number of limitations associated with traditional linear models. In this workshop, you will learn when it is important to use a mixed effects model to analyze your data. We will walk you through the steps to conduct a linear mixed model analysis, check its assumptions,​ report results, and visually represent your model in R. We will also build on the previous workshop to combine knowledge on linear mixed models and extend it to generalized linear mixed effect models.
  
-**Link to new [[https://​qcbsrworkshops.github.io/​workshop06/workshop06-en/workshop06-en.html|Rmarkdown presentation]]**+**Link to new [[https://​qcbsrworkshops.github.io/​workshop07/pres-en/workshop07-pres-en.html|Rmarkdown presentation]]**
  
 Link to old [[http://​prezi.com/​5syafj73u0qe/​|Prezi presentation]] Link to old [[http://​prezi.com/​5syafj73u0qe/​|Prezi presentation]]
  
-Link to old Link to old [[http://​prezi.com/​suxdvftadzl4/​|Prezi presentation covering GLMMs]]+Link to old [[http://​prezi.com/​suxdvftadzl4/​|Prezi presentation covering GLMMs]]
  
 Download the R script and data for this lesson: ​ Download the R script and data for this lesson: ​