Week 2 : BP models & interactions in GLM. Lab: markdown

Admission requirements What you need to read before coming to class on Tuesday .
Chapter: 2 - Between-Person Analysis and Interpretation of Interactions
Lecture: Interpreting General Linear Models slides | watch | download

Tuesay session

Mplus & Centering

Extra credit

You can earn extra credit by researching and sharing online resources that could be of use in preparing this week’s report. This week’s theme : online resources for learning markdown. Vote only if you find this resource useful

Non-competitive EC

  • post as a reply to “EXTRA CREDIT” comment thread at the bottom of this page
  • get 1 point if posted before 23:59 Friday

Competitive EC

  • best 5 posts (measured by the end of the lab on Friday) get another 1 EC points

Report due

Assignment Summarize the first two chapters in a markdown report. Use this cheatsheet to ensure that your report contains at least:

  • 3 different headings
  • 1 ordered list
  • 1 unordered list
  • 1 definition list
  • 3 kinds of emphasis
  • 1 link to a webpage
  • 1 image call
  • 2 tables

NOTE: You will not be graded on the content, but be prepare to discuss your work with the class.


Markdown Resourses

Screenshot Links & Descriptions
md1 1 Markdwon Tutorial by Garen Torikian
md2 2 Markdown Cheatsheet by Adam Pritchard
md3 3 Markdown Syntax Cheat Sheet by Mark Boszko
md4 4 The R Markdown Cheat sheet for dynamic reporting in RStudio by RStudio Blog
md5 5 Markdown quick reference from Wordpress
md6 6 Video tutorial by Stevan Wing
md7 7 Markdown syntax guide by Fletcher T. Penney
md8 8 Markdown syntax reference by Squarespace
md9 9 Markdown table generator by Table Generator

Learning objectives: Concepts

Basic

  • simple effect
  • main effect
  • contrast
  • interaction

Intermediate

  • General Linear Model
  • use of dummy variables

Advanced

  • Three-way interactions

Learning objectives: Skills

Basic

  • load data
  • basic file types in MPlus
  • reading the output

Intermediate

  • re-center a continuous predictor
  • write dummy variable

Advanced

  • plot interactions