R/minimalExamples.R
minimalExamples.Rd
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
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.
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 .
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...