The datasets present minimal examples that are analyzed with an Analysis of Frequency Data method (described in Laurencelle and Cousineau (2023) . The five datasets are

  • 'minimalBSExample': an example with a single factor (state of residency)

  • 'twoWayExample': an example with two factors, Class and Difficulty

  • 'minimalWSExample': an example with a within-subject design (three measurements)

  • 'twoWayWithinExample': an example with two within-subject factors

  • 'minimalMxExample': a mixed design having one within and one between-subject factors

  • 'minimalMxExampleCompiled': a mixed design having one within and one between-subject factors but available in a compiled format (more compact).

minimalBSExample

twoWayExample

minimalWSExample

twoWayWithinExample

minimalMxExample

minimalMxExampleCompiled

Format

Objects of class data.frame:

An object of class data.frame with 6 rows and 4 columns.

An object of class data.frame with 19 rows and 3 columns.

An object of class data.frame with 30 rows and 6 columns.

An object of class data.frame with 27 rows and 5 columns.

An object of class data.frame with 4 rows and 5 columns.

References

Laurencelle L, Cousineau D (2023). “Analysis of proportions using arcsine transform with any experimental design.” Frontiers in Psychology, 13, 1045436. doi:10.3389/fpsyg.2022.1045436 .

Examples

library(ANOPA)

# the twoWayExample data with proportions per Classes and Difficulty levels 
twoWayExample
#>   Class Difficulty success total
#> 1 First       Easy      11    12
#> 2 First   Moderate       9    12
#> 3 First  Difficult       6    12
#> 4  Last       Easy      10    12
#> 5  Last   Moderate       8    12
#> 6  Last  Difficult       3    12

# perform an anopa on this dataset
w <- anopa( {success;total} ~ Difficulty * Class, twoWayExample) 

# We analyse the proportions by Difficulty for each Class
e <- emProportions(w, ~ Difficulty | Class)
#> Not yet programmed...