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Bonte Bruno
AIAT
Commits
50ed4b3a
Commit
50ed4b3a
authored
Feb 14, 2020
by
Bonte Bruno
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add a specific file for leem analysis
parent
3563cd4e
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data/alldata-expe-lem.csv
data/alldata-expe-lem.csv
+2640
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data/summarized-expe-lem.csv
data/summarized-expe-lem.csv
+12
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iat-leem-analysis.R
iat-leem-analysis.R
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data/alldata-expe-lem.csv
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50ed4b3a
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data/summarized-expe-lem.csv
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50ed4b3a
"Id","Date","Block4.m","Block4.sd","Block7.m","Block7.sd","diff","full.sd","d"
"100786589","02-05-2020 21:22",1199.43243243243,490.402926204596,957.846153846154,426.485363385646,-241.586278586279,471.561645055786,-0.512311128606948
"1017239621","02-10-2020 15:05",831.9,214.016989500534,800.3,193.316029287504,-31.6,203.257372544444,-0.155467915404104
"1022760865","02-13-2020 17:56",1662.56756756757,722.040224354285,1028.8,292.414370547284,-633.767567567568,626.42783451277,-1.01171680543299
"103374404","02-10-2020 10:44",936.225,535.366229191732,607.1,474.236567782602,-329.125,535.833358195533,-0.614230142573352
"108624355","02-10-2020 17:56",759.075,210.264959527564,1099.5,396.886472174187,340.425,359.064579140955,0.948088504899177
"124789236","02-10-2020 13:59",685.96,308.902422565228,757.75,396.915573166665,71.79,356.580968277319,0.201328748269503
"1299045547","02-10-2020 16:25",1296.97368421053,531.823252840392,996.179487179487,403.522507804699,-300.794197031039,491.960071094806,-0.611419939755788
"156960961","02-11-2020 10:04",1064.5,321.955881672613,873.825,274.051453853057,-190.675,312.174303946215,-0.610796588923769
"1576459677","02-05-2020 15:04",1007.575,445.584484348712,900.55,269.714088885972,-107.025,369.903249196087,-0.289332413901738
"168900812","02-10-2020 14:09",907.15,434.456191176144,805,319.572230108328,-102.15,382.413348338342,-0.267119336821952
"1831964311","02-10-2020 10:17",1070.15625,467.760768009364,1079.94736842105,486.898898844093,9.79111842105272,474.816203080807,0.0206208599401701
"1832683201","02-01-2020 15:06",989.5,444.428183463212,825.9,318.103256901406,-163.6,392.73202123882,-0.416569037288953
"1873310289","02-10-2020 22:02",792.85,314.629823190723,1126.43243243243,349.144393922927,333.582432432432,369.708018302271,0.90228617156931
"19072949","02-04-2020 16:17",868.575,219.158049455241,797.315789473684,304.570153926601,-71.2592105263159,264.927420806224,-0.268976349482664
"1907490474","02-10-2020 17:12",843.75,351.740343479063,832.75,360.529009466182,-11,353.943695014484,-0.031078389458385
"2043193029","02-10-2020 16:58",1198.55263157895,405.496272343877,1032.375,448.945184678657,-166.177631578947,433.686482805223,-0.383174570035148
"222109674","02-03-2020 11:06",943.128205128205,352.016834188305,907.815789473684,254.652795449885,-35.3124156545209,306.340456670398,-0.115271799351382
"223517612","02-02-2020 16:58",719,169.297038306898,811.538461538462,294.820806070921,92.5384615384615,242.577798480162,0.381479517574356
"238416187","02-01-2020 17:21",1078.6,448.134469288073,996.2,360.923473670187,-82.3999999999999,406.409334089958,-0.202751248773634
"26285618","02-10-2020 10:23",653.5,155.991452757301,872.55,182.08337763304,219.05,201.314602022163,1.08809792136134
"284411184","02-10-2020 14:10",1021.10526315789,366.429432716232,1002.825,431.58657137328,-18.2802631578946,398.68181086386,-0.0458517611282169
"291727775","02-10-2020 22:09",966.333333333333,477.517336876415,622,217.088921873043,-344.333333333333,465.076850388919,-0.740379429862798
"303732253","02-01-2020 22:52",620.205882352941,183.401824023804,644.325,184.013152748969,24.1191176470588,182.871300714338,0.13189121285212
"365542128","02-10-2020 10:02",900.775,454.743009277965,1000.38461538462,367.876238870501,99.6096153846154,414.534613900202,0.240292636717175
"370634186","02-03-2020 18:39",1063.65,427.427579710804,897.675,358.958135370572,-165.975,400.967499038027,-0.413936292587792
...
...
@@ -24,17 +32,21 @@
"4830243","02-05-2020 12:22",1023.95,409.626030197526,984.975,381.855556494391,-38.975,393.958487299347,-0.0989317434615518
"487953098","02-01-2020 12:41",797.2,345.707909910026,913.128205128205,314.853698647414,115.928205128205,333.848525591469,0.347247917069032
"51558243","02-10-2020 14:59",1284.91891891892,567.970283767772,NA,NA,NA,567.970283767772,NA
"520123005","02-10-2020 23:16",900.825,264.611169745055,689.525,216.947351228652,-211.3,262.877878707821,-0.803795287144918
"593253971","02-10-2020 13:14",751.825,361.507377482617,1009.44736842105,559.117049939839,257.622368421053,482.913309062055,0.533475395245211
"606820006","02-01-2020 11:33",1024.02564102564,418.389109195803,1298.16666666667,742.356630378329,274.141025641026,471.895187172711,0.580936261044535
"61088246","02-10-2020 13:24",994.552631578947,461.461175045061,927.128205128205,502.043203188477,-67.4244264507423,480.464612304981,-0.140331722095578
"631328297","02-10-2020 13:42",780.525,192.600554822536,946.6,423.961947978039,166.075,337.682490512514,0.491808147197509
"641947421","02-10-2020 17:06",789.85,208.294361483073,838.625,269.232211992471,48.775,240.427059059183,0.202868180440512
"642119270","02-02-2020 13:17",839.375,214.476546742445,804.65,234.344098304729,-34.725,223.886640266617,-0.155100813334139
"649738704","02-03-2020 17:04",823.175,325.729232173454,670.55,169.259919983499,-152.625,269.107232109094,-0.567153096569798
"658909377","02-01-2020 12:09",893.368421052632,382.017575727881,760.717948717949,373.883456983868,-132.650472334683,381.312302149216,-0.347878816358707
"672360277","02-10-2020 16:18",891.078947368421,340.350167977196,887.125,385.704894998289,-3.95394736842104,361.962217208712,-0.0109236466692908
"71044925","02-01-2020 18:03",720.7,297.101225950918,658.25,189.538948030511,-62.45,249.596432494385,-0.250203896649865
"741228137","02-10-2020 13:39",953.3,461.696492603151,990.526315789474,409.854867974355,37.2263157894737,434.781407676171,0.0856207628298591
"762436101","02-10-2020 22:22",912.875,326.644571793335,936.775,391.981389373762,23.9,358.705858661348,0.0666284071556351
"785118707","02-01-2020 18:06",1047.25641025641,482.35942691539,1270.4358974359,418.296280974936,223.179487179487,462.37231517702,0.48268349953877
"792321511","02-12-2020 13:35",974.125,347.228084907771,908,267.83261133086,-66.125,309.904327570358,-0.213372302731034
"794559200","02-10-2020 15:14",725.425,224.2903209613,724.7,246.167047722914,-0.724999999999909,233.988009199974,-0.00309844937131073
"805273055","02-01-2020 15:50",811.775,295.630095229035,929,289.523304052962,117.225,296.65751867444,0.395152634336721
"821663749","02-01-2020 14:46",1230.35135135135,597.422296956601,806.95,251.229280303971,-423.401351351351,496.780377709683,-0.852290811693021
...
...
iat-leem-analysis.R
0 → 100644
View file @
50ed4b3a
#load basic libraries for graphs
library
(
dplyr
)
library
(
tidyr
)
library
(
ggplot2
)
library
(
stringr
)
library
(
RColorBrewer
)
#set working directory where this source file is
setwd
(
"/home/bruno/git/aiat"
)
#################################################################
## Pour ploter les distributions des temps de réactions à partir#
##### des résultats bruts #######
#################################################################
alldata
<-
read.table
(
"data/alldata-expe-lem.csv"
,
sep
=
","
,
dec
=
"."
,
header
=
T
)
%>%
tbl_df
()
iat_scores
<-
alldata
%>%
filter
(
reactionTime
<
3000
)
%>%
filter
(
reactionTime
>
300
)
%>%
filter
(
trial
==
4
|
(
trial
==
7
))
%>%
group_by
(
id
)
%>%
mutate
(
full.sd
=
sd
(
reactionTime
))
%>%
group_by
(
id
,
trial
,
full.sd
)
%>%
summarise
(
mRT
=
mean
(
reactionTime
),
sdRT
=
sd
(
reactionTime
))
%>%
gather
(
variable
,
value
,
-
id
,
-
full.sd
,
-
trial
)
%>%
unite
(
block
,
trial
,
variable
)
%>%
spread
(
block
,
value
,
sep
=
""
)
%>%
mutate
(
d
=
round
((
block7_mRT
-
block4_mRT
)
/
full.sd
,
digits
=
5
))
iat_scores_train
<-
alldata
%>%
filter
(
reactionTime
<
3000
)
%>%
filter
(
reactionTime
>
300
)
%>%
filter
(
trial
==
3
|
(
trial
==
6
))
%>%
group_by
(
id
)
%>%
mutate
(
full.sd
=
sd
(
reactionTime
))
%>%
group_by
(
id
,
trial
,
full.sd
)
%>%
summarise
(
mRT
=
mean
(
reactionTime
),
sdRT
=
sd
(
reactionTime
))
%>%
gather
(
variable
,
value
,
-
id
,
-
full.sd
,
-
trial
)
%>%
unite
(
block
,
trial
,
variable
)
%>%
spread
(
block
,
value
,
sep
=
""
)
%>%
mutate
(
d
=
round
((
block6_mRT
-
block3_mRT
)
/
full.sd
,
digits
=
5
))
alldata
%>%
filter
(
reactionTime
<
3000
)
%>%
filter
(
reactionTime
>
300
)
%>%
filter
(
trial
==
4
|
(
trial
==
7
))
%>%
mutate
(
category
=
recode_factor
(
category
,
"A"
=
"Appropriation"
,
"P"
=
"Partage"
,
"1"
=
"Moi"
,
"2"
=
"PasMoi"
))
%>%
mutate
(
trial
=
as.factor
(
trial
))
%>%
left_join
(
iat_scores
,
by
=
'id'
)
%>%
mutate
(
lab
=
paste0
(
"id: "
,
id
,
"\n(d="
,
d
,
")"
))
%>%
ggplot
()
+
geom_histogram
(
aes
(
x
=
reactionTime
,
fill
=
trial
),
position
=
"dodge"
)
+
facet_wrap
(
~
lab
,
scales
=
"free_x"
)
+
ggsave
(
"per-trial-reaction-times-alldata.pdf"
,
height
=
21
,
width
=
29.7
,
units
=
"cm"
)
iat_scores
%>%
mutate
(
lab
=
(
as.factor
(
id
)))
%>%
ggplot
()
+
geom_bar
(
aes
(
x
=
reorder
(
lab
,
d
),
y
=
d
),
stat
=
"identity"
)
+
theme
(
axis.text.x
=
element_text
(
angle
=
90
,
hjust
=
1
,
vjust
=
0.5
))
+
xlab
(
"id"
)
+
ggsave
(
"scores-alldata.pdf"
,
height
=
21
/
2
,
width
=
29.7
/
2
,
units
=
"cm"
)
iat_scores
%>%
select
(
id
,
d
)
%>%
mutate
(
session
=
"Test"
)
%>%
union
(
iat_scores_train
%>%
select
(
id
,
d
)
%>%
mutate
(
session
=
"Training"
))
%>%
group_by
(
id
)
%>%
mutate
(
order
=
mean
(
d
))
%>%
mutate
(
lab
=
(
as.factor
(
id
)))
%>%
ggplot
()
+
geom_bar
(
aes
(
x
=
reorder
(
lab
,
order
),
y
=
d
,
fill
=
session
),
stat
=
"identity"
,
position
=
"dodge"
)
+
theme
(
axis.text.x
=
element_text
(
angle
=
90
,
hjust
=
1
,
vjust
=
0.5
))
+
xlab
(
"id"
)
+
ggsave
(
"scores-alldata-ntrain.pdf"
,
height
=
21
/
2
,
width
=
29.7
/
1.5
,
units
=
"cm"
)
iat_scores
%>%
select
(
id
,
d
)
%>%
mutate
(
session
=
"Test"
)
%>%
union
(
iat_scores_train
%>%
select
(
id
,
d
)
%>%
mutate
(
session
=
"Training"
))
%>%
ggplot
()
+
geom_density
(
aes
(
x
=
d
,
color
=
session
),
bins
=
15
,
bw
=
0.1
)
+
ggsave
(
"scores-density-alldata-n-train.pdf"
,
height
=
21
/
2
,
width
=
29.7
/
2
,
units
=
"cm"
)
iat_scores
%>%
select
(
id
,
d
)
%>%
mutate
(
session
=
"Test"
)
%>%
union
(
iat_scores_train
%>%
select
(
id
,
d
)
%>%
mutate
(
session
=
"Training"
))
%>%
ggplot
()
+
geom_histogram
(
aes
(
x
=
d
,
fill
=
session
),
position
=
"dodge"
,
bins
=
15
,
bw
=
0.1
)
+
ggsave
(
"scores-histo-alldata-n-train.pdf"
,
height
=
21
/
2
,
width
=
29.7
/
2
,
units
=
"cm"
)
iat_scores
%>%
ggplot
()
+
geom_density
(
aes
(
d
),
bins
=
15
,
bw
=
0.1
)
+
ggsave
(
"scores-density-alldata.pdf"
,
height
=
21
/
2
,
width
=
29.7
/
2
,
units
=
"cm"
)
iat_scores
%>%
ggplot
()
+
geom_histogram
(
aes
(
d
),
bins
=
15
,
bw
=
0.1
)
+
ggsave
(
"scores-histo-alldata.pdf"
,
height
=
21
/
2
,
width
=
29.7
/
2
,
units
=
"cm"
)
items
<-
list
(
c
(
"compétition"
,
"gain"
,
"profit"
,
"winner"
,
"performance"
),
c
(
"coopération"
,
"équité"
,
"égalité"
,
"gentillesse"
,
"solidarité"
),
c
(
"je"
,
"soi"
,
"mon"
),
c
(
"autre"
,
"eux"
,
"pas moi"
))
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