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Short Unsupervised

A Short Introduction to ASReml-R (ASReml_01)


Description
In this course we will focus on the fundamentals of using ASReml-R version 4 for the analyses of experimental data to fit models for biological studies. ASReml-R is statistical software (and library in R) that fits linear mixed models (LMM) using REML methodology and calculates BLUE and BLUP values.

Statistical aspects related to fitting LMMs, such as random versus fixed effects, heterogeneous error structures, multilevel models, and correlated observations, among others will be addressed together with understanding of the ASReml-R code for proper construction/specification of linear models (and their variance structure) and extracting relevant information.

For this course, it is recommended that you have some basic understanding of linear models and be familiar with the statistical package R. You will have 30 days of access to this material to complete your training.

Do you have a license for ASReml-R version 4? As participant of this training you have access to a free license of ASReml-R for the duration of the training course 30 days. Once purchased you will be sent a license and link to download the software within 24 hours. Please note this will ONLY be sent to the email from which you signed up.
Content
  • WELCOME TO A SHORT INTRODUCTION TO ASREML-R
  • OUTLINE OF TOPICS
  • GETTING READY FOR CLASS
  • SESSION 1: INTRODUCTION
  • VIDEO 1: Fitting a Linear Model for a Randomized Block Design
  • SESSION 1: SUMMARY AND ADDITIONAL MATERIALS
  • SESSION 2: INTRODUCTION
  • VIDEO 2: Specifying Fixed or Random Effects for a Block Design sample
  • SESSION 2: SUMMARY AND ADDITIONAL MATERIALS
  • SESSION 3: INTRODUCTION
  • VIDEO 3: Modelling Heterogeneous Error Structures
  • SESSION 3: SUMMARY AND ADDITIONAL MATERIALS
  • SESSION 4: INTRODUCTION
  • VIDEO 4: Fitting a Multilevel Model for Hierarchical Structure
  • SESSION 4: SUMMARY AND ADDITIONAL MATERIALS
  • SESSION 5: INTRODUCTION
  • VIDEO 5: Incorporating Pedigree Information in a Genetic Model
  • SESSION 5: SUMMARY AND ADDITIONAL MATERIALS
  • SESSION 6: INTRODUCTION
  • VIDEO 6: Accounting for Correlated Observations in a Linear Mixed Model
  • SESSION 6: SUMMARY AND ADDITIONAL MATERIALS
  • SESSION 7: INTRODUCTION
  • VIDEO 7: Modelling Binomial Data with GLM and GLMM
  • SESSION 7: SUMMARY AND ADDITIONAL MATERIALS
  • CLOSING REMARKS
Completion rules
  • All units must be completed
  • Leads to a certification with a duration: Forever