About this document
1
Binary Regression
1.1
When to use this model?
1.2
Description of the Model
1.3
similarities to the chi-squared test
1.4
Example 1: Simple example but bad model fit
1.4.1
Organizing data
1.4.2
Fitting Model
1.4.3
Model validering via gof-pakken. Gerne via kkholst på github.
1.4.4
Hypothesis test
1.4.5
Parameter estimates with emmeans.
1.5
Example 2: Multiple variables and correct model fit
1.5.1
Organizing data
1.5.2
Fitting Model
1.5.3
Model validering via gof-pakken. Gerne via kkholst på github.
1.5.4
Hypothesis test
2
Linear regression
3
Model Validation
3.1
Why and How
3.2
Sample size of one
3.2.1
Data Example 1: Weight of Crabs
3.2.2
Data Example 2: Salary Data from Connecticut - log transformation
3.3
Sample size of two
3.3.1
Simulated data example
3.3.2
Data Example 3: Lean body mass and physical strength for men and women
3.4
Linear nomral models (regression, ANOVA, ANCOVA)
3.4.1
Data Example 4: pillbugs (oneway ANOVA)
3.4.2
Data Example 5: Lean body mass and physical strength for men and women (continued)
3.4.3
Data Example 5: birthwt
3.5
Miscellaneous
3.5.1
Intepretation of results when transforming
3.5.2
Boxcox
3.5.3
Shapiro Wilk hypothesis test for normality
4
One-way analysis of variance
4.1
When to use this model?
4.2
Organisation of data and data import
4.3
Data exploration
4.4
Fitting the model
4.4.1
… with default reference group
4.4.2
.. without a reference group
4.4.3
… with user defined reference group
4.4.4
Digging more into the output from
summary()
4.5
Validating the model
4.5.1
Why do I need to valide the model?
4.5.2
How do I validate the model assumptions?
4.5.3
What to do if the model is not valid?
4.6
Extracting estimates with
emmeans()
4.7
Reporting the results
4.7.1
Tables
4.7.2
Figures
4.7.3
Stat methods section
4.8
Alternatives and related statistical methods
4.8.1
Analysis on logtransformed scale
4.8.2
Relation to t-tests and non-parametric testing
4.8.3
When data are not normally distributed
5
Poisson regression
6
Analysis of repeated measures
7
Two-way analysis of variance
7.1
When to use this model?
7.2
Organizing data
7.3
Data exploration
7.4
Fitting model
7.5
Validating the model
7.5.1
Why do I need to valide the model?
7.5.2
How do I validate the model assumptions?
7.6
Hypothesis test
7.7
Extracting estimates with
emmeans()
7.8
Writing article/report
7.8.1
How to write method section
7.8.2
How to write results section
7.9
Miscellaneous
7.9.1
Why to not use ANOVA tables
A short introduction to common statistical data analysis techniques
Chapter 5
Poisson regression