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
0.1
Staff
Coordinator:
dr. Caspar J. van Lissa
Lecturers
dr. Caspar J. van Lissa
Computer labs
Danielle McCool
Laura Hofstee