add a specific file for leem analysis

data/summarized-expe-lem.csv

 "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

+#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"))
+
+