• TCSM
  • Course
    • 0.1 Staff
    • 0.2 Learning goals
    • 0.3 Theory Construction and Statistical Modeling
    • 0.4 Course overview
    • 0.5 Adaptations related to the coronavirus measures
      • 0.5.1 Why not in-person meetings?
      • 0.5.2 Why learning in groups?
      • 0.5.3 Why use take home assignments for assessment?
    • 0.6 Grading
    • 0.7 Assignments
    • 0.8 Rules for the take-home assignments
    • 0.9 Statement on fair grading during corona
    • 0.10 Attendance
    • 0.11 Literature
    • 0.12 Reading questions
    • 0.13 Preparations
  • 1 Preparing for the course
    • 1.1 Installing software
      • 1.1.1 1. Installing R
      • 1.1.2 2. Installing RStudio
      • 1.1.3 3. Installing packages
      • 1.1.4 Get started
      • 1.1.5 Starting a new project in Rstudio
      • 1.1.6 Code conventions
      • 1.1.7 Getting Help
    • 1.2 Getting the course data
    • 1.3 R tutorial for beginners (optional)
      • 1.3.1 Who R you?
      • 1.3.2 RStudio
      • 1.3.3 Loading data
      • 1.3.4 Explore your data
    • 1.4 Plotting the data (optional)
      • 1.4.1 A histogram
      • 1.4.2 A boxplot
      • 1.4.3 Scatterplot
  • 2 Getting your data into R
    • 2.1 Using R projects
    • 2.2 Importing Excel Files
      • 2.2.1 Inspect the data
    • 2.3 Importing SPSS Files
    • 2.4 Data manipulation (optional)
      • 2.4.1 Converting to factors
      • 2.4.2 Selecting specific cases
      • 2.4.3 Changing cell values
  • 3 Week 1 - Overview
  • 4 Week 1 - Reading questions
  • 5 Week 1 - Home
    • 5.0.1 Question 1.a
    • 5.0.2 Question 1.b
    • 5.0.3 Question 1.c.
    • 5.0.4 Question 1.d.
    • 5.0.5 Question 1.e.
    • 5.0.6 Question 1.f.
  • 6 Week 1 - Class
    • 6.1 Loading data
    • 6.2 Section 1
      • 6.2.1 Question 1.a
      • 6.2.2 Question 1.b
      • 6.2.3 Question 1.c
      • 6.2.4 Question 1.d
      • 6.2.5 Question 1.e
      • 6.2.6 Question 1.f
      • 6.2.7 Question 1.g
      • 6.2.8 Question 1.h
      • 6.2.9 Question 1.i
      • 6.2.10 Question 1.j
    • 6.3 Section 2
      • 6.3.1 Research question 1 (ANOVA): Does talking on the phone interfere with people’s driving skills?
      • 6.3.2 Question 2.a
      • 6.3.3 Question 2.b
      • 6.3.4 Question 2.c
      • 6.3.5 Question 2.d
      • 6.3.6 Question 2.e
      • 6.3.7 Research question 2 (ANCOVA): Are there differences in reaction time between the conditions when controlling for age?
      • 6.3.8 Question 2.f
      • 6.3.9 Question 2.g
      • 6.3.10 Question 2.h
      • 6.3.11 Question 2.i
    • 6.4 Section 3
      • 6.4.1 Question 3.a
      • 6.4.2 Question 3.b
      • 6.4.3 Question 3.c
      • 6.4.4 Question 3.d
      • 6.4.5 Question 3.e
      • 6.4.6 Question 3.f
      • 6.4.7 Question 3.g
      • 6.4.8 Question 3.h
      • 6.4.9 Question 3.i
      • 6.4.10 Question 3.j
      • 6.4.11 Question 3.k
      • 6.4.12 Question 3.l
      • 6.4.13 Question 3.m
  • 7 Week 1 - Formative test
  • 8 Week 2 - Overview
  • 9 Week 2 - Reading questions
  • 10 Week 2 - Home
    • 10.0.1 Question 1.a
    • 10.0.2 Question 1.b
    • 10.0.3 Question 1.c
    • 10.0.4 Question 1.d
    • 10.0.5 Question 1.e
    • 10.0.6 Question 1.f
    • 10.0.7 Question 1.g
    • 10.0.8 Question 1.h
    • 10.0.9 Question 1.i
    • 10.0.10 Question 1.j
  • 11 Week 2 - Class
    • 11.0.1 Loading the data
    • 11.0.2 Question 1
    • 11.0.3 Question 2
    • 11.0.4 Question 3
    • 11.0.5 Question 4
    • 11.0.6 Question 5
    • 11.0.7 Question 6
    • 11.0.8 Question 7
    • 11.0.9 Question 8
    • 11.0.10 Question 9
    • 11.0.11 Question 10
    • 11.0.12 Question 11
  • 12 Week 2 - Formative test
  • 13 Week 3 - Overview
  • 14 Week 3 - Reading questions
  • 15 Week 3 - Home
    • 15.0.1 Get started with lavaan
    • 15.0.2 Regression models in lavaan
    • 15.0.3 Conceptual model
    • 15.0.4 Lavaan syntax
    • 15.0.5 Performing the analysis
    • 15.0.6 Viewing the output
    • 15.0.7 Plotting the output
  • 16 Week 3 - Class
    • 16.0.1 Question 1
    • 16.0.2 Question 2
    • 16.0.3 Question 3
    • 16.0.4 Question 4
    • 16.0.5 Question 5
    • 16.0.6 Question 6
    • 16.0.7 Question 7
    • 16.0.8 Question 8
    • 16.0.9 Question 9
    • 16.0.10 Optional
    • 16.0.11 Question 10
  • 17 Week 3 - Formative test
  • 18 Week 4 - Overview
  • 19 Week 4 - Reading questions
  • 20 Week 4 - Home
    • 20.0.1 Question 1
    • 20.0.2 Question 2
    • 20.0.3 Question 3
    • 20.0.4 Question 4
    • 20.0.5 Question 5
    • 20.0.6 Question 6
    • 20.0.7 Question 7
    • 20.0.8 Question 8
    • 20.0.9 Additional options
    • 20.0.10 Question 9
    • 20.0.11 Question 10
  • 21 Week 4 - Class
    • 21.0.1 Specify basic model
    • 21.0.2 How to run multi-group model
    • 21.0.3 Question 1
    • 21.0.4 Question 2
    • 21.0.5 Question 3
    • 21.0.6 Question 4
    • 21.0.7 Imposing constraints
    • 21.0.8 Stepwise approach
    • 21.0.9 Question 5
    • 21.0.10 Question 6
  • 22 Week 4 - Formative test
  • 23 Week 5 - Overview
  • 24 Week 5 - Reading questions
  • 25 Week 5 - Home
    • 25.0.1 Specify model
    • 25.0.2 Question 1
    • 25.0.3 Question 2
    • 25.0.4 Question 3
    • 25.0.5 Estimating indirect effects
    • 25.0.6 Question 4
    • 25.0.7 Question 5
    • 25.0.8 Question 6
    • 25.0.9 Difference between parameters
    • 25.0.10 Bootstrapping
    • 25.0.11 Question 7
  • 26 Week 5 - Class
    • 26.0.1 The analysis
    • 26.0.2 Question 1
    • 26.0.3 Dummy coding
    • 26.0.4 Question 2
    • 26.0.5 Question 3
    • 26.0.6 Question 4
    • 26.0.7 Question 5
    • 26.0.8 Question 6
    • 26.0.9 Question 7
  • 27 Week 5 - Formative test
  • 28 Week 6 - Overview
  • 29 Week 6 - Reading questions
  • 30 Week 6 - Home
    • 30.0.1 Question 1
    • 30.0.2 Question 2
    • 30.0.3 Question 3
    • 30.0.4 Question 4
    • 30.0.5 Question 5
    • 30.0.6 Question 6
    • 30.0.7 Question 7
    • 30.0.8 Question 8
    • 30.0.9 Question 9
    • 30.0.10 Question 10
    • 30.0.11 Question 11
  • 31 Week 6 - Class
    • 31.0.1 Question 1
    • 31.0.2 Question 2
    • 31.0.3 Question 3
    • 31.0.4 Question 4
    • 31.0.5 Question 5
    • 31.0.6 Question 6
    • 31.0.7 Specific differences
    • 31.0.8 Question 7
    • 31.0.9 Question 8
    • 31.0.10 Results table
    • 31.0.11 Question 9
    • 31.0.12 Question 10
    • 31.0.13 Question 12
    • 31.0.14 Question 13
  • 32 Week 6 - Formative test
  • 33 Week 7 - Overview
  • 34 Week 7 - Putting it all together
    • 34.0.1 Loading the data
    • 34.0.2 Question 1
    • 34.0.3 Question 2
    • 34.0.4 Question 3
    • 34.0.5 Question 4
    • 34.0.6 Question 5
    • 34.0.7 Question 6
    • 34.0.8 Moderated mediation
    • 34.0.9 Question 7
    • 34.0.10 Measurement invariance
    • 34.0.11 Question 8
    • 34.0.12 Question 9

Theory Construction and Statistical Modeling

0.5 Adaptations related to the coronavirus measures

The corona crisis is challenging all of us to rethink how we teach and learn. But aside from the challenges, it also offers opportunities. In adapting this course, we kept two goals in mind: increasing the alignment between the way of teaching and the learning goals, and ensuring high-quality interaction among students and between the students and teachers while still using online communication. Based on these goals, we made the following changes:

  1. During the course, you will be working in learning teams to promote interaction among students and peer support
  2. The two in-person exams (4 hours each) are replaced with take-home assignments: Two group assignments, and one individual assignment.

0.5.1 Why not in-person meetings?

When the courses were scheduled, it was not yet clear what direction the university wanted to take. Every teacher could make a choice: Online-only, or hybrid education. At that time, I chose the online format, because:

  1. Last year, the online version of this course was very successful
  2. This elective course attracts diverse students with complex schedules; many expressed a preference for the flexibility of an online course
  3. Due to the 75 student maximum on lecture halls, it is very difficult to schedule courses. Doing this course in person would mean that we have meetings on varying days at different times. That would likely create scheduling conflicts for many of you.

0.5.2 Why learning in groups?

Contact with fellow students is a key aspect of the university experience. During this time of social distancing, it is important to find new ways to stay in touch with fellow students. There are also aspects of learning in groups that can really improve your knowledge, like peer feedback. The groups are made randomly when the course starts, but you can switch with a consenting member of another group in the first week.

0.5.3 Why use take home assignments for assessment?

Assignments are a suitable form of assessment for a skills-based course like TCSM. It also takes a lot of the pressure off because you can work at your own pace. This course used to have two 4-hour exams; not exactly corona-proof. Using take-home assignments entrusts you with the responsibility to make this assignment in good faith, without instrumental assistance or plagiarism, so I kindly ask you to make good on this trust, and hand in original work to show what you’ve learned.