bayes4psy-datasets {bayes4psy} | R Documentation |
Datasets for bayes4psy examples Example datasets for use in rstanarm examples and vignettes. The datasets were extracted from the internal MBLab http://www.mblab.si repository. MBLab is a research lab at the Faculty of Arts, Department of Psychology, University of Ljubljana, Slovenia.
Description
Datasets for bayes4psy examples Example datasets for use in rstanarm examples and vignettes. The datasets were extracted from the internal MBLab http://www.mblab.si repository. MBLab is a research lab at the Faculty of Arts, Department of Psychology, University of Ljubljana, Slovenia.
Format
adaptation_level_small
-
Small dataset on subjects picking up weights and determining their weights from 1..10.
Source: Internal MBLab repository.
50 obs. of 3 variables
-
sequence
sequence index. -
weight
actual weight of the object. -
response
subject's estimation of weight.
-
adaptation_level
-
Data on subjects picking up weights and determining their weights from 1..10.
Source: Internal MBLab repository.
2900 obs. of 6 variables
-
subject
subject index. -
group
group index. -
part
first or second part of the experiment. -
sequence
sequence index. -
weight
actual weight of the object. -
response
subject's estimation of weight.
-
#'
after_images_opponent_process
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Colors predicted by the opponent process theory.
Source: Internal MBLab repository.
6 obs. of 7 variables
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stimuli
name of the color stimuli. -
r
value of the R component in the RGB model. -
g
value of the G component in the RGB model. -
b
value of the B component in the RGB model. -
h
value of the H component in the HSV model. -
s
value of the S component in the HSV model. -
v
value of the V component in the HSV model.
-
#'
after_images_opponent_stimuli
-
Stimuli used in the after images experiment.
Source: Internal MBLab repository.
6 obs. of 7 variables
-
r_s
value of the R component in the RGB model. -
g_s
value of the G component in the RGB model. -
b_s
value of the B component in the RGB model. -
stimuli
name of the color stimuli. -
h_s
value of the H component in the HSV model. -
s_s
value of the S component in the HSV model. -
v_s
value of the V component in the HSV model.
-
#'
after_images_trichromatic
-
Colors predicted by the trichromatic theory.
Source: Internal MBLab repository.
6 obs. of 7 variables
-
stimuli
name of the color stimuli. -
r
value of the R component in the RGB model. -
g
value of the G component in the RGB model. -
b
value of the B component in the RGB model. -
h
value of the H component in the HSV model. -
s
value of the S component in the HSV model. -
v
value of the V component in the HSV model.
-
#'
after_images
-
Data gathered by the after images experiment.
Source: Internal MBLab repository.
1311 obs. of 12 variables
-
subject
subject index. -
rt
reaction time. -
r
value of the R component in the RGB model of subject's response. -
g
value of the G component in the RGB model of subject's response. -
b
value of the B component in the RGB model of subject's response. -
stimuli
name of the color stimuli. -
r_s
value of the R component in the RGB model of the shown stimulus -
g_s
value of the G component in the RGB model of the shown stimulus -
b_s
value of the B component in the RGB model of the shown stimulus -
h_s
value of the H component in the HSV model of the shown stimulus -
s_s
value of the S component in the HSV model of the shown stimulus -
v_s
value of the V component in the HSV model of the shown stimulus
-
#'
flanker
-
Data gathered by the flanker experiment.
Source: Internal MBLab repository.
8256 obs. of 5 variables
-
subject
subject index. -
group
group index. -
congruencty
type of stimulus. -
result
was subject's reponse correct or wrong? -
rt
reaction time.
-
#'
stroop_extended
-
All the data gathered by the Stroop experiment.
Source: Internal MBLab repository.
41068 obs. of 5 variables
-
subject
subject ID. -
cond
type of condition. -
rt
reaction time. -
acc
was subject's reponse correct or wrong? -
age
age of subject.
-
#'
stroop_simple
-
All the data gathered by the Stroop experiment.
Source: Internal MBLab repository.
61 obs. of 5 variables
-
subject
subject ID. -
reading_neutral
average response time for reading neutral stimuli. -
naming_neutral
average response time for naming neutral stimuli. -
reading_incongruent
average response time for reading incongruent stimuli. -
naming_incongruent
average response time for naming incongruent stimuli.
-
Examples
# Example of Bayesian bootstraping on 'adaptation_level_small' dataset
# linear function of seqence vs. response
lm_statistic <- function(data) {
lm(sequence ~ response, data)$coef
}
# load data
data <- adaptation_level_small
# bootstrap
data_bootstrap <- b_bootstrap(data, lm_statistic, n1=1000, n2=1000)