Agronomy and Horticulture Department
Analysis of Augmented Block Design Using R, Part 1: An Introduction to an Augmented Design Approach in Plant Breeding
Date of this Version
2014
Document Type
Article
Citation
Plant and Soil Sciences eLibrary (PASSeL) Lessons.
Abstract
Objectives
When planning any science research project to gain information for a particular goal or objective, much thought is placed into what is called the experimental design or layout of the experiment. This is important to ensure the researcher is able to obtain useful data which can later be analyzed and provide information as to whether or not the scientific hypothesis being tested is supported or rejected. In this eLesson series we will look at a plant breeding experiment which uses the Augmented Design and utilize tools in R to analyze the data.
After completing this lesson, you will be able to :
- Understand details of the Augmented Design used in the experiment discussed in this eLesson.
- Describe critical elements of a Linear Mixed Model viz. the Fixed Effects and the Random Effects.
- Explain how Linear Mixed Modeling plays a role in the research scenario depicted in this lesson.
Modules:
COinS
Comments
Copyright 2014, the authors. Used by permission.
This project was supported in part by the National Research Initiative Competitive Grants CAP project 2011-68002-30029 from the USDA National Institute of Food and Agriculture, administered by the University of California-Davis and by the National Science Foundation (NSF), Division of Undergraduate Education, National SMETE Digital Library Program, Award #0938034, administered by the University of Nebraska. Any opinions, findings, conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the USDA or NSF.
This eLesson was supported in part by the National Research Initiative Competitive Grants CAP project 2011-68002-30029 from the USDA National Institute of Food and Agriculture, administered by the University of California-Davis. Any opinions, findings, conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the USDA-NIFA.