Data Cleaning & Basic Statistics HW
Sophie Sabo
2023-05-30
1 Data Cleaning
1.1 Load Libraries
library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.2 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.2 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors1.2 Import Data
df <- read.csv(file="EAMMi2-Data1.2.csv", header=T)1.3 Viewing Data
names(df)## [1] "StartDate" "EndDate" "Status"
## [4] "Progress" "Duration..in.seconds." "Finished"
## [7] "RecordedDate" "ResponseId" "RecipientLastName"
## [10] "RecipientFirstName" "RecipientEmail" "ExternalReference"
## [13] "DistributionChannel" "informedconsent" "moa1.1_1"
## [16] "moa1.1_2" "moa1.1_3" "moa1.1_4"
## [19] "moa1.1_5" "moa1.1_6" "moa1.1_7"
## [22] "moa1.1_8" "moa1.1_9" "moa1.1_10"
## [25] "moa1.2_1" "moa1.2_2" "moa1.2_3"
## [28] "moa1.2_4" "moa1.2_5" "moa1.2_6"
## [31] "moa1.2_7" "moa1.2_8" "moa1.2_9"
## [34] "moa1.2_10" "moa2.1_1" "moa2.1_2"
## [37] "moa2.1_3" "moa2.1_4" "moa2.1_5"
## [40] "moa2.1_6" "moa2.1_7" "moa2.1_8"
## [43] "moa2.1_9" "moa2.1_10" "moa2.2_1"
## [46] "moa2.2_2" "moa2.2_3" "moa2.2_4"
## [49] "moa2.2_5" "moa2.2_6" "moa2.2_7"
## [52] "moa2.2_8" "moa2.2_9" "moa2.2_10"
## [55] "adult_Q" "MOA_IMP_biascheck" "MOA_ach_biascheck"
## [58] "MOA_IMP_dummy" "MOA.ACH_dummy" "Q65_First.Click"
## [61] "Q65_Last.Click" "Q65_Page.Submit" "Q65_Click.Count"
## [64] "IDEA_1" "IDEA_2" "IDEA_3"
## [67] "IDEA_4" "IDEA_5" "IDEA_6"
## [70] "IDEA_7" "IDEA_8" "IDEA.biascheck"
## [73] "IDEA.bias.dummy" "Q66_First.Click" "Q66_Last.Click"
## [76] "Q66_Page.Submit" "Q66_Click.Count" "politics"
## [79] "party" "president" "Q74_First.Click"
## [82] "Q74_Last.Click" "Q74_Page.Submit" "Q74_Click.Count"
## [85] "swb_1" "swb_2" "swb_3"
## [88] "swb_4" "swb_5" "swb_6"
## [91] "Q67_First.Click" "Q67_Last.Click" "Q67_Page.Submit"
## [94] "Q67_Click.Count" "mindful_1" "mindful_2"
## [97] "mindful_3" "mindful_4" "mindful_5"
## [100] "mindful_6" "mindful_7" "mindful_8"
## [103] "mindful_9" "mindful_10" "mindful_11"
## [106] "mindful_12" "mindful_13" "mindful_14"
## [109] "mindful_15" "mindful_biascheck" "mindful_bias_dummy"
## [112] "Q68_First.Click" "Q68_Last.Click" "Q68_Page.Submit"
## [115] "Q68_Click.Count" "belong_1" "belong_2"
## [118] "belong_3" "belong_4" "belong_5"
## [121] "belong_6" "belong_7" "belong_8"
## [124] "belong_9" "belong_10" "belnow"
## [127] "belong_biascheck" "belong_bias_dummy" "Q72_First.Click"
## [130] "Q72_Last.Click" "Q72_Page.Submit" "Q72_Click.Count"
## [133] "efficacy_1" "efficacy_2" "efficacy_3"
## [136] "efficacy_4" "efficacy_5" "efficacy_6"
## [139] "efficacy_7" "efficacy_8" "efficacy_9"
## [142] "efficacy_10" "efficacy_biascheck" "efficacy_bias_dummy"
## [145] "Q77_First.Click" "Q77_Last.Click" "Q77_Page.Submit"
## [148] "Q77_Click.Count" "support_1" "support_2"
## [151] "support_3" "support_4" "support_5"
## [154] "support_6" "support_7" "support_8"
## [157] "support_9" "support_10" "support_11"
## [160] "support_12" "support_biascheck" "support_bias_dummy"
## [163] "Q96_First.Click" "Q96_Last.Click" "Q96_Page.Submit"
## [166] "Q96_Click.Count" "SocMedia_1" "SocMedia_2"
## [169] "SocMedia_3" "SocMedia_4" "SocMedia_5"
## [172] "SocMedia_6" "SocMedia_7" "SocMedia_8"
## [175] "SocMedia_9" "SocMedia_10" "SocMedia_11"
## [178] "SocMedia_biascheck" "SocMedia_bias_dummy" "Q80_First.Click"
## [181] "Q80_Last.Click" "Q80_Page.Submit" "Q80_Click.Count"
## [184] "usdream_1" "usdream_2" "usdream_3"
## [187] "Q73_First.Click" "Q73_Last.Click" "Q73_Page.Submit"
## [190] "Q73_Click.Count" "freq" "transgres"
## [193] "relation" "relation_10_TEXT" "fault"
## [196] "feel" "common" "attenion2"
## [199] "Q78_First.Click" "Q78_Last.Click" "Q78_Page.Submit"
## [202] "Q78_Click.Count" "transgres_1" "transgres_2"
## [205] "transgres_3" "transgres_4" "Q79_First.Click"
## [208] "Q79_Last.Click" "Q79_Page.Submit" "Q79_Click.Count"
## [211] "NPI1" "NPI2" "NPI3"
## [214] "NPI4" "NPI5" "NPI6"
## [217] "NPI7" "NPI8" "NPI9"
## [220] "NPI10" "NPI11" "NPI12"
## [223] "NPI13" "exploit_1" "exploit_2"
## [226] "exploit_3" "NPI_biascheck" "NPI_bias_dummy"
## [229] "Q76_First.Click" "Q76_Last.Click" "Q76_Page.Submit"
## [232] "Q76_Click.Count" "Q11" "Q14_1"
## [235] "Q14_2" "Q14_3" "Q14_4"
## [238] "Q14_5" "Q14_6" "Q14_6_TEXT"
## [241] "Q10_1" "Q10_2" "Q10_3"
## [244] "Q10_4" "Q10_5" "Q10_6"
## [247] "Q10_7" "Q10_8" "Q10_9"
## [250] "Q10_10" "Q10_11" "Q10_12"
## [253] "Q10_13" "Q10_14" "Q10_15"
## [256] "Q71_First.Click" "Q71_Last.Click" "Q71_Page.Submit"
## [259] "Q71_Click.Count" "physSx_1" "physSx_2"
## [262] "physSx_3" "physSx_4" "physSx_5"
## [265] "physSx_6" "physSx_7" "physSx_8"
## [268] "physSx_9" "physSx_10" "physSx_11"
## [271] "physSx_12" "physSx_13" "phys_sx_biaschec"
## [274] "phys_sym_bias_dummy." "Q70_First.Click" "Q70_Last.Click"
## [277] "Q70_Page.Submit" "Q70_Click.Count" "stress_1"
## [280] "stress_2" "stress_3" "stress_4"
## [283] "stress_5" "stress_6" "stress_7"
## [286] "stress_8" "stress_9" "stress_10"
## [289] "stress_biascheck" "stress_bias_dummy" "Q69_First.Click"
## [292] "Q69_Last.Click" "Q69_Page.Submit" "Q69_Click.Count"
## [295] "marriage1_1" "marriage1_2" "marriage1_3"
## [298] "marriage1_4" "marriage2" "marriage3"
## [301] "marriage4" "marriage5" "Q75_First.Click"
## [304] "Q75_Last.Click" "Q75_Page.Submit" "Q75_Click.Count"
## [307] "school" "sex" "age"
## [310] "edu" "sibling" "race"
## [313] "race_6_TEXT" "Q82" "Q83"
## [316] "income" "place2" "Q80"
## [319] "place" "Q81" "Q81_First.Click"
## [322] "Q81_Last.Click" "Q81_Page.Submit" "Q81_Click.Count"
## [325] "comments" "affiliation" "response_bias_SUM"
## [328] "school_coded"head(df)## StartDate EndDate Status Progress Duration..in.seconds. Finished
## 1 12/02/16 12/02/16 0 100 1839 1
## 2 11/16/16 11/16/16 0 100 1467 1
## 3 11/09/16 11/09/16 0 99 2185 0
## 4 11/07/16 11/07/16 0 100 2904 1
## 5 11/18/16 11/18/16 0 100 1229 1
## 6 11/07/16 11/07/16 0 100 2068 1
## RecordedDate ResponseId RecipientLastName RecipientFirstName
## 1 12/2/2016 5:38 R_BJN3bQqi1zUMid3 NA NA
## 2 11/16/2016 11:53 R_2TGbiBXmAtxywsD NA NA
## 3 11/16/2016 1:22 R_12G7bIqN2wB2N65 NA NA
## 4 11/7/2016 4:54 R_39pldNoon8CePfP NA NA
## 5 11/18/2016 0:30 R_1QiKb2LdJo1Bhvv NA NA
## 6 11/7/2016 14:42 R_pmwDTZyCyCycXwB NA NA
## RecipientEmail ExternalReference DistributionChannel informedconsent moa1.1_1
## 1 NA NA anonymous 1 4
## 2 NA NA anonymous 1 4
## 3 NA NA anonymous 1 4
## 4 NA NA anonymous 1 4
## 5 NA NA anonymous 1 4
## 6 NA NA anonymous 1 4
## moa1.1_2 moa1.1_3 moa1.1_4 moa1.1_5 moa1.1_6 moa1.1_7 moa1.1_8 moa1.1_9
## 1 4 3 2 2 3 2 1 4
## 2 4 4 2 3 3 4 3 3
## 3 4 4 1 1 4 2 3 4
## 4 3 3 1 1 2 1 1 1
## 5 4 4 1 1 3 1 1 4
## 6 3 4 2 3 4 2 1 3
## moa1.1_10 moa1.2_1 moa1.2_2 moa1.2_3 moa1.2_4 moa1.2_5 moa1.2_6 moa1.2_7
## 1 3 2 1 2 1 1 1 2
## 2 3 1 1 2 2 1 1 1
## 3 3 2 1 1 1 1 1 2
## 4 1 1 1 1 1 1 1 2
## 5 3 2 1 2 1 3 3 1
## 6 4 1 1 1 1 1 1 1
## moa1.2_8 moa1.2_9 moa1.2_10 moa2.1_1 moa2.1_2 moa2.1_3 moa2.1_4 moa2.1_5
## 1 3 3 2 4 4 4 4 3
## 2 1 2 3 3 4 2 4 4
## 3 3 3 3 4 2 2 4 3
## 4 3 2 3 4 2 2 4 3
## 5 1 3 2 4 4 3 4 4
## 6 1 1 3 4 4 4 4 2
## moa2.1_6 moa2.1_7 moa2.1_8 moa2.1_9 moa2.1_10 moa2.2_1 moa2.2_2 moa2.2_3
## 1 4 4 4 3 2 2 1 1
## 2 3 2 4 2 1 3 1 2
## 3 3 4 4 3 2 2 1 1
## 4 2 4 2 3 2 2 1 1
## 5 3 4 4 3 3 3 3 3
## 6 4 3 4 4 4 2 1 1
## moa2.2_4 moa2.2_5 moa2.2_6 moa2.2_7 moa2.2_8 moa2.2_9 moa2.2_10 adult_Q
## 1 3 2 3 3 2 2 1 1
## 2 2 1 2 2 2 2 1 1
## 3 2 1 2 3 1 1 1 1
## 4 2 1 2 2 2 2 1 1
## 5 3 3 2 3 3 2 3 1
## 6 2 1 2 2 1 2 1 1
## MOA_IMP_biascheck MOA_ach_biascheck MOA_IMP_dummy MOA.ACH_dummy
## 1 64 38 0 0
## 2 62 33 0 0
## 3 61 33 0 0
## 4 46 32 0 0
## 5 62 47 0 0
## 6 67 27 0 0
## Q65_First.Click Q65_Last.Click Q65_Page.Submit Q65_Click.Count IDEA_1 IDEA_2
## 1 37.139 307.731 308.890 45 3 4
## 2 120.026 336.428 338.177 58 4 4
## 3 27.705 154.447 155.544 47 4 4
## 4 19.656 297.285 298.509 43 4 4
## 5 12.867 121.932 122.254 46 4 4
## 6 15.652 223.372 225.431 50 3 4
## IDEA_3 IDEA_4 IDEA_5 IDEA_6 IDEA_7 IDEA_8 IDEA.biascheck IDEA.bias.dummy
## 1 4 3 4 4 4 4 30 0
## 2 4 4 3 4 4 4 31 0
## 3 4 4 4 4 3 3 30 0
## 4 3 3 4 4 4 4 30 0
## 5 3 4 3 3 3 4 28 0
## 6 3 3 4 4 3 2 26 0
## Q66_First.Click Q66_Last.Click Q66_Page.Submit Q66_Click.Count politics party
## 1 44.705 86.585 87.514 11 2 3
## 2 19.927 65.200 67.162 13 1 4
## 3 23.170 51.401 52.408 11 2 8
## 4 27.467 172.797 174.119 9 8 8
## 5 23.952 52.176 53.355 9 1 8
## 6 9.475 72.935 73.937 13 8 8
## president
## 1
## 2 None, but I was a US Citizen and had a gun next to my head, I would vote for Trump
## 3 Hillary Clinton
## 4 Hillary Clinton
## 5 Sanders
## 6 No one.
## Q74_First.Click Q74_Last.Click Q74_Page.Submit Q74_Click.Count swb_1 swb_2
## 1 13.052 40.445 46.399 2 4 6
## 2 4.899 28.125 55.107 6 3 4
## 3 34.868 48.402 56.371 4 1 2
## 4 66.886 119.219 135.295 4 5 6
## 5 23.614 32.221 35.338 4 2 5
## 6 12.314 41.232 54.436 6 4 4
## swb_3 swb_4 swb_5 swb_6 Q67_First.Click Q67_Last.Click Q67_Page.Submit
## 1 5 5 3 3 9.627 40.388 41.198
## 2 5 5 4 4 8.607 29.115 29.955
## 3 2 2 2 2 37.656 53.240 54.603
## 4 6 5 6 3 13.587 55.197 56.150
## 5 5 3 2 5 6.798 22.246 23.138
## 6 6 5 1 4 7.927 44.108 48.227
## Q67_Click.Count mindful_1 mindful_2 mindful_3 mindful_4 mindful_5 mindful_6
## 1 7 4 2 2 2 4 1
## 2 7 2 2 2 1 3 1
## 3 9 2 3 1 2 3 1
## 4 7 2 2 1 2 2 1
## 5 7 4 5 3 2 4 1
## 6 7 1 4 3 3 5 1
## mindful_7 mindful_8 mindful_9 mindful_10 mindful_11 mindful_12 mindful_13
## 1 2 2 2 2 2 4 1
## 2 1 1 2 2 1 2 1
## 3 2 2 5 3 2 1 1
## 4 2 2 3 2 2 3 3
## 5 4 2 1 2 2 6 5
## 6 5 6 3 5 1 3 2
## mindful_14 mindful_15 mindful_biascheck mindful_bias_dummy Q68_First.Click
## 1 2 4 36 0 32.692
## 2 1 5 27 0 13.184
## 3 1 4 33 0 48.022
## 4 2 4 33 0 110.432
## 5 2 5 48 0 81.124
## 6 4 5 51 0 33.458
## Q68_Last.Click Q68_Page.Submit Q68_Click.Count belong_1 belong_2 belong_3
## 1 154.123 157.391 15 4 2 4
## 2 76.856 77.629 22 2 3 1
## 3 142.665 143.398 20 4 4 2
## 4 255.734 257.134 17 3 4 1
## 5 134.499 135.848 16 4 3 3
## 6 212.770 213.511 25 2 3 2
## belong_4 belong_5 belong_6 belong_7 belong_8 belong_9 belong_10 belnow
## 1 4 4 2 5 2 4 3 4
## 2 5 4 4 2 4 5 4 4
## 3 5 4 4 2 3 4 4 2
## 4 5 4 5 2 4 4 4 4
## 5 4 4 5 1 3 2 3 4
## 6 5 4 5 1 4 4 4 3
## belong_biascheck belong_bias_dummy Q72_First.Click Q72_Last.Click
## 1 38 0 8.221 80.460
## 2 38 0 6.774 65.987
## 3 38 0 5.697 71.192
## 4 40 0 6.096 86.373
## 5 36 0 58.613 121.436
## 6 37 0 6.124 70.638
## Q72_Page.Submit Q72_Click.Count efficacy_1 efficacy_2 efficacy_3 efficacy_4
## 1 82.781 13 4 3 4 3
## 2 67.158 18 3 3 3 4
## 3 72.176 13 3 3 1 2
## 4 87.231 14 4 1 2 3
## 5 122.620 11 3 3 2 3
## 6 72.503 15 3 2 3 2
## efficacy_5 efficacy_6 efficacy_7 efficacy_8 efficacy_9 efficacy_10
## 1 3 4 3 3 4 3
## 2 4 4 3 3 3 4
## 3 2 3 1 3 2 2
## 4 2 4 2 3 4 3
## 5 3 3 3 3 4 3
## 6 1 3 2 3 3 2
## efficacy_biascheck efficacy_bias_dummy Q77_First.Click Q77_Last.Click
## 1 34 0 15.372 104.315
## 2 34 0 11.711 74.768
## 3 22 0 38.964 179.667
## 4 28 0 16.050 168.886
## 5 30 0 32.150 59.030
## 6 24 0 6.259 69.817
## Q77_Page.Submit Q77_Click.Count support_1 support_2 support_3 support_4
## 1 105.195 11 7 4 6 5
## 2 75.558 21 7 7 7 6
## 3 182.727 13 6 6 5 2
## 4 170.530 10 6 6 7 3
## 5 60.273 11 6 6 5 5
## 6 70.970 13 7 7 6 6
## support_5 support_6 support_7 support_8 support_9 support_10 support_11
## 1 6 6 7 7 7 4 6
## 2 7 6 6 7 7 7 7
## 3 7 5 5 3 6 6 5
## 4 7 6 5 4 6 6 6
## 5 6 6 7 6 6 6 7
## 6 7 2 2 1 1 7 6
## support_12 support_biascheck support_bias_dummy Q96_First.Click
## 1 7 72 0 12.241
## 2 7 81 0 7.482
## 3 6 62 0 18.845
## 4 5 67 0 30.307
## 5 6 72 0 13.096
## 6 2 54 0 24.841
## Q96_Last.Click Q96_Page.Submit Q96_Click.Count SocMedia_1 SocMedia_2
## 1 91.497 92.381 17 4 2
## 2 34.247 35.467 19 3 2
## 3 74.388 76.037 14 3 3
## 4 150.285 151.869 18 4 2
## 5 43.727 45.041 12 3 3
## 6 110.942 111.636 18 1 1
## SocMedia_3 SocMedia_4 SocMedia_5 SocMedia_6 SocMedia_7 SocMedia_8 SocMedia_9
## 1 5 3 5 5 5 4 5
## 2 4 2 1 1 1 1 2
## 3 4 2 3 4 4 2 3
## 4 5 2 2 4 4 1 3
## 5 5 2 2 4 4 2 4
## 6 2 1 1 1 2 1 1
## SocMedia_10 SocMedia_11 SocMedia_biascheck SocMedia_bias_dummy
## 1 5 4 47 0
## 2 4 2 23 0
## 3 3 3 34 0
## 4 4 4 35 0
## 5 4 4 37 0
## 6 1 1 13 0
## Q80_First.Click Q80_Last.Click Q80_Page.Submit Q80_Click.Count usdream_1
## 1 17.470 59.573 60.431 11 4
## 2 10.768 45.340 47.007 15 4
## 3 30.059 66.498 68.018 12 2
## 4 112.432 161.455 163.036 11 1
## 5 22.246 53.406 55.275 12 3
## 6 5.361 89.568 90.785 15 1
## usdream_2 usdream_3 Q73_First.Click Q73_Last.Click Q73_Page.Submit
## 1 4 1 14.144 24.073 27.558
## 2 4 1 5.240 27.206 36.973
## 3 2 1 5.671 16.751 19.891
## 4 3 1 71.153 82.926 98.687
## 5 4 1 21.293 32.533 35.448
## 6 1 2 6.771 37.203 45.268
## Q73_Click.Count freq
## 1 3 3
## 2 5 4
## 3 3 6
## 4 3 3
## 5 3 4
## 6 4 2
## transgres
## 1 told my friend that something he did was wrong and hurtful to somebody else.
## 2 got very passive
## 3 you don't want to see me
## 4 I tried to excuse myself and said I was sorry
## 5 Got angry.
## 6 why didn't you tell him?
## relation relation_10_TEXT fault feel common attenion2 Q78_First.Click
## 1 4 6 3 3 7 22.366
## 2 7 2 1,4,5,6,7,8 4 7 6.174
## 3 5 3 6 5 7 9.705
## 4 4 3 10,4,6 2 7 58.517
## 5 7 2 5,6 3 NA 5.647
## 6 6 3 1 4 7 15.862
## Q78_Last.Click Q78_Page.Submit Q78_Click.Count transgres_1 transgres_2
## 1 148.934 153.134 12 3 1
## 2 72.626 74.609 22 4 3
## 3 109.167 111.847 10 3 1
## 4 195.290 199.227 14 4 2
## 5 61.894 65.304 13 4 2
## 6 174.894 177.914 21 1 3
## transgres_3 transgres_4 Q79_First.Click Q79_Last.Click Q79_Page.Submit
## 1 1 1 16.239 27.208 28.488
## 2 2 1 20.400 31.697 32.941
## 3 4 1 57.079 77.311 82.171
## 4 1 1 23.005 49.246 50.303
## 5 2 1 11.727 23.987 25.130
## 6 1 1 14.701 35.077 40.711
## Q79_Click.Count NPI1 NPI2 NPI3 NPI4 NPI5 NPI6 NPI7 NPI8 NPI9 NPI10 NPI11
## 1 4 1 1 1 2 1 2 2 1 2 2 1
## 2 4 2 2 1 2 1 2 1 1 1 1 2
## 3 5 2 1 1 2 1 2 1 1 1 2 2
## 4 5 2 2 1 2 1 2 2 1 1 2 1
## 5 8 1 2 1 2 1 2 2 2 1 2 1
## 6 6 2 2 2 1 2 2 2 2 1 2 1
## NPI12 NPI13 exploit_1 exploit_2 exploit_3 NPI_biascheck NPI_bias_dummy
## 1 2 1 2 2 2 19 0
## 2 1 1 4 4 3 18 0
## 3 2 1 5 5 3 19 0
## 4 2 1 2 1 2 20 0
## 5 2 2 5 4 3 21 0
## 6 2 2 1 1 2 23 0
## Q76_First.Click Q76_Last.Click Q76_Page.Submit Q76_Click.Count Q11 Q14_1
## 1 25.575 141.688 142.668 16 2 2
## 2 10.473 103.989 105.050 35 2 2
## 3 29.957 129.786 132.515 22 2 2
## 4 49.912 222.748 223.703 18 2 2
## 5 5.315 108.076 109.093 25 2 2
## 6 5.353 94.716 98.083 25 2 2
## Q14_2 Q14_3 Q14_4 Q14_5 Q14_6 Q14_6_TEXT Q10_1 Q10_2 Q10_3 Q10_4 Q10_5 Q10_6
## 1 2 2 2 2 2 NA NA NA NA NA NA
## 2 2 2 2 2 NA NA NA NA NA NA NA
## 3 2 2 1 2 2 4 3 4 2 4 5
## 4 2 2 2 2 2 NA NA NA NA NA NA
## 5 2 2 2 2 NA NA NA NA NA NA NA
## 6 2 2 2 2 2 NA NA NA NA NA NA
## Q10_7 Q10_8 Q10_9 Q10_10 Q10_11 Q10_12 Q10_13 Q10_14 Q10_15 Q71_First.Click
## 1 NA NA NA NA NA NA NA NA NA 5.199
## 2 NA NA NA NA NA NA NA NA NA 6.497
## 3 3 1 4 1 3 1 4 2 2 4.533
## 4 NA NA NA NA NA NA NA NA NA 7.430
## 5 NA NA NA NA NA NA NA NA NA 5.020
## 6 NA NA NA NA NA NA NA NA NA 15.872
## Q71_Last.Click Q71_Page.Submit Q71_Click.Count physSx_1 physSx_2 physSx_3
## 1 28.239 28.669 7 3 1 1
## 2 23.457 24.600 8 2 2 1
## 3 115.299 116.410 21 3 1 1
## 4 122.984 128.490 12 2 3 2
## 5 7.996 17.581 6 1 1 1
## 6 32.719 33.562 7 1 2 2
## physSx_4 physSx_5 physSx_6 physSx_7 physSx_8 physSx_9 physSx_10 physSx_11
## 1 2 1 2 1 2 2 2 2
## 2 1 3 1 1 3 2 1 1
## 3 3 2 2 1 3 2 1 2
## 4 3 1 2 1 2 1 1 2
## 5 2 1 1 1 1 2 1 1
## 6 1 2 2 1 3 1 2 2
## physSx_12 physSx_13 phys_sx_biaschec phys_sym_bias_dummy. Q70_First.Click
## 1 3 2 24 0 13.703
## 2 3 3 24 0 5.209
## 3 3 3 27 0 36.694
## 4 3 2 25 0 47.764
## 5 2 1 16 0 4.561
## 6 3 2 24 0 10.062
## Q70_Last.Click Q70_Page.Submit Q70_Click.Count stress_1 stress_2 stress_3
## 1 54.318 60.887 16 2 4 5
## 2 27.841 28.982 17 4 5 5
## 3 79.053 80.519 18 4 4 5
## 4 77.308 79.068 13 2 4 4
## 5 18.707 20.343 14 4 3 3
## 6 80.372 82.827 18 3 3 5
## stress_4 stress_5 stress_6 stress_7 stress_8 stress_9 stress_10
## 1 3 3 3 4 3 3 3
## 2 4 3 3 2 2 4 4
## 3 2 1 5 2 2 4 4
## 4 3 4 5 4 2 2 2
## 5 4 3 4 3 3 4 4
## 6 2 3 5 2 1 3 2
## stress_biascheck stress_bias_dummy Q69_First.Click Q69_Last.Click
## 1 33 0 10.383 100.428
## 2 36 0 9.729 43.281
## 3 33 0 42.213 89.329
## 4 32 0 43.206 180.767
## 5 35 0 63.797 76.765
## 6 29 0 16.412 94.543
## Q69_Page.Submit Q69_Click.Count marriage1_1 marriage1_2 marriage1_3
## 1 101.287 14 10 25 30
## 2 44.423 13 10 25 35
## 3 91.194 12 1 1 59
## 4 182.932 12 0 0 60
## 5 77.998 13 25 25 25
## 6 95.709 15 13 33 21
## marriage1_4 marriage2 marriage3 marriage4 marriage5 Q75_First.Click
## 1 35 2 20 1 2 20.229
## 2 30 3 19 1 1 11.100
## 3 39 2 19 1 1 40.807
## 4 40 1 16 1 1 74.778
## 5 25 2 14 3 1 21.347
## 6 33 3 17 1 1 19.366
## Q75_Last.Click Q75_Page.Submit Q75_Click.Count school sex
## 1 164.560 165.870 32 ACG 2
## 2 60.223 61.354 17 ACG,Deree 1
## 3 160.366 165.459 23 American College of Greece 1
## 4 155.971 156.974 13 American College of Greece 2
## 5 48.802 49.742 11 American College of Greece 1
## 6 181.747 183.288 25 American College of Greece 2
## age edu sibling race race_6_TEXT Q82 Q83 income place2 Q80 place Q81
## 1 20 2 2 1 3 NA 3 2 NA NA Greece
## 2 23 5 2 1 3 NA 3 2 NA NA Greece
## 3 23 2 5 1 3 NA 1 2 NA NA Greece
## 4 22 2 3,5,7 6 Greek 3 NA 1 2 NA NA Greece
## 5 18 2 3,5,7 1 3 NA 6 2 NA NA Greece
## 6 23 2 2,4 1 3 NA 1 2 NA NA Greece
## Q81_First.Click Q81_Last.Click Q81_Page.Submit Q81_Click.Count
## 1 0.000 0.000 5.781 0
## 2 2.424 2.424 6.621 1
## 3 0.000 0.000 9.294 0
## 4 2.679 2.679 5.803 1
## 5 1.632 1.632 5.500 1
## 6 2.766 2.766 6.995 1
## comments
## 1 I have completed this survey
## 2 i have completed this survey
## 3 Didn't know my household income.\nI have completed the last question about disability wrong. I read "not" the moment I pressed ">>"
## 4 I have completed this survey
## 5 i have completed this survey
## 6 The question saying "Select" was funny.
## affiliation response_bias_SUM school_coded
## 1 acgreece 0 acgreece
## 2 acgreece 0 acgreece
## 3 acgreece 0 acgreece
## 4 acgreece 0 acgreece
## 5 acgreece 0 acgreece
## 6 acgreece 0 acgreecestr(df)## 'data.frame': 3182 obs. of 328 variables:
## $ StartDate : chr "12/02/16" "11/16/16" "11/09/16" "11/07/16" ...
## $ EndDate : chr "12/02/16" "11/16/16" "11/09/16" "11/07/16" ...
## $ Status : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Progress : int 100 100 99 100 100 100 99 99 100 100 ...
## $ Duration..in.seconds.: int 1839 1467 2185 2904 1229 2068 1656 1839 1160 2134 ...
## $ Finished : int 1 1 0 1 1 1 0 0 1 1 ...
## $ RecordedDate : chr "12/2/2016 5:38" "11/16/2016 11:53" "11/16/2016 1:22" "11/7/2016 4:54" ...
## $ ResponseId : chr "R_BJN3bQqi1zUMid3" "R_2TGbiBXmAtxywsD" "R_12G7bIqN2wB2N65" "R_39pldNoon8CePfP" ...
## $ RecipientLastName : logi NA NA NA NA NA NA ...
## $ RecipientFirstName : logi NA NA NA NA NA NA ...
## $ RecipientEmail : logi NA NA NA NA NA NA ...
## $ ExternalReference : logi NA NA NA NA NA NA ...
## $ DistributionChannel : chr "anonymous" "anonymous" "anonymous" "anonymous" ...
## $ informedconsent : int 1 1 1 1 1 1 1 1 1 1 ...
## $ moa1.1_1 : int 4 4 4 4 4 4 4 4 4 3 ...
## $ moa1.1_2 : int 4 4 4 3 4 3 4 4 4 2 ...
## $ moa1.1_3 : int 3 4 4 3 4 4 4 4 4 3 ...
## $ moa1.1_4 : int 2 2 1 1 1 2 3 3 4 1 ...
## $ moa1.1_5 : int 2 3 1 1 1 3 3 3 4 1 ...
## $ moa1.1_6 : int 3 3 4 2 3 4 4 4 4 2 ...
## $ moa1.1_7 : int 2 4 2 1 1 2 4 3 1 3 ...
## $ moa1.1_8 : int 1 3 3 1 1 1 4 3 2 3 ...
## $ moa1.1_9 : int 4 3 4 1 4 3 4 4 4 4 ...
## $ moa1.1_10 : int 3 3 3 1 3 4 3 3 4 3 ...
## $ moa1.2_1 : int 2 1 2 1 2 1 1 2 2 2 ...
## $ moa1.2_2 : int 1 1 1 1 1 1 1 2 2 2 ...
## $ moa1.2_3 : int 2 2 1 1 2 1 2 2 2 2 ...
## $ moa1.2_4 : int 1 2 1 1 1 1 1 1 1 1 ...
## $ moa1.2_5 : int 1 1 1 1 3 1 1 1 1 1 ...
## $ moa1.2_6 : int 1 1 1 1 3 1 1 1 2 2 ...
## $ moa1.2_7 : int 2 1 2 2 1 1 3 3 1 3 ...
## $ moa1.2_8 : int 3 1 3 3 1 1 3 3 3 3 ...
## $ moa1.2_9 : int 3 2 3 2 3 1 3 3 3 3 ...
## $ moa1.2_10 : int 2 3 3 3 2 3 3 3 1 3 ...
## $ moa2.1_1 : int 4 3 4 4 4 4 4 4 4 3 ...
## $ moa2.1_2 : int 4 4 2 2 4 4 4 4 4 3 ...
## $ moa2.1_3 : int 4 2 2 2 3 4 3 4 4 3 ...
## $ moa2.1_4 : int 4 4 4 4 4 4 4 4 4 4 ...
## $ moa2.1_5 : int 3 4 3 3 4 2 4 4 4 3 ...
## $ moa2.1_6 : int 4 3 3 2 3 4 4 3 4 4 ...
## $ moa2.1_7 : int 4 2 4 4 4 3 4 4 2 4 ...
## $ moa2.1_8 : int 4 4 4 2 4 4 3 4 4 4 ...
## $ moa2.1_9 : int 3 2 3 3 3 4 4 4 4 4 ...
## $ moa2.1_10 : int 2 1 2 2 3 4 2 4 2 2 ...
## $ moa2.2_1 : int 2 3 2 2 3 2 2 2 3 3 ...
## $ moa2.2_2 : int 1 1 1 1 3 1 1 1 1 2 ...
## $ moa2.2_3 : int 1 2 1 1 3 1 1 1 3 3 ...
## $ moa2.2_4 : int 3 2 2 2 3 2 2 3 3 3 ...
## $ moa2.2_5 : int 2 1 1 1 3 1 1 1 2 2 ...
## $ moa2.2_6 : int 3 2 2 2 2 2 2 2 3 3 ...
## $ moa2.2_7 : int 3 2 3 2 3 2 1 2 1 3 ...
## $ moa2.2_8 : int 2 2 1 2 3 1 2 3 2 2 ...
## $ moa2.2_9 : int 2 2 1 2 2 2 2 2 3 3 ...
## $ moa2.2_10 : int 1 1 1 1 3 1 1 1 1 2 ...
## $ adult_Q : int 1 1 1 1 1 1 1 1 1 2 ...
## $ MOA_IMP_biascheck : int 64 62 61 46 62 67 73 74 71 59 ...
## $ MOA_ach_biascheck : int 38 33 33 32 47 27 34 39 40 48 ...
## $ MOA_IMP_dummy : int 0 0 0 0 0 0 0 0 0 0 ...
## $ MOA.ACH_dummy : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Q65_First.Click : num 37.1 120 27.7 19.7 12.9 ...
## $ Q65_Last.Click : num 308 336 154 297 122 ...
## $ Q65_Page.Submit : num 309 338 156 299 122 ...
## $ Q65_Click.Count : int 45 58 47 43 46 50 45 42 47 47 ...
## $ IDEA_1 : int 3 4 4 4 4 3 4 4 4 4 ...
## $ IDEA_2 : int 4 4 4 4 4 4 3 3 4 4 ...
## $ IDEA_3 : int 4 4 4 3 3 3 4 3 3 2 ...
## $ IDEA_4 : int 3 4 4 3 4 3 4 4 2 2 ...
## $ IDEA_5 : int 4 3 4 4 3 4 3 3 4 4 ...
## $ IDEA_6 : int 4 4 4 4 3 4 4 2 4 4 ...
## $ IDEA_7 : int 4 4 3 4 3 3 3 2 3 3 ...
## $ IDEA_8 : int 4 4 3 4 4 2 3 3 3 4 ...
## $ IDEA.biascheck : int 30 31 30 30 28 26 28 24 27 27 ...
## $ IDEA.bias.dummy : int 0 0 0 0 0 0 0 0 0 0 ...
## $ Q66_First.Click : num 44.7 19.9 23.2 27.5 24 ...
## $ Q66_Last.Click : num 86.6 65.2 51.4 172.8 52.2 ...
## $ Q66_Page.Submit : num 87.5 67.2 52.4 174.1 53.4 ...
## $ Q66_Click.Count : int 11 13 11 9 9 13 9 8 8 9 ...
## $ politics : int 2 1 2 8 1 8 4 2 8 4 ...
## $ party : int 3 4 8 8 8 8 4 1 3 8 ...
## $ president : chr "" "None, but I was a US Citizen and had a gun next to my head, I would vote for Trump" "Hillary Clinton" "Hillary Clinton" ...
## $ Q74_First.Click : num 13.1 4.9 34.9 66.9 23.6 ...
## $ Q74_Last.Click : num 40.4 28.1 48.4 119.2 32.2 ...
## $ Q74_Page.Submit : num 46.4 55.1 56.4 135.3 35.3 ...
## $ Q74_Click.Count : int 2 6 4 4 4 6 3 3 3 3 ...
## $ swb_1 : int 4 3 1 5 2 4 4 5 5 5 ...
## $ swb_2 : int 6 4 2 6 5 4 4 5 5 4 ...
## $ swb_3 : int 5 5 2 6 5 6 5 6 5 6 ...
## $ swb_4 : int 5 5 2 5 3 5 4 5 5 4 ...
## $ swb_5 : int 3 4 2 6 2 1 1 6 5 6 ...
## $ swb_6 : int 3 4 2 3 5 4 4 6 5 4 ...
## $ Q67_First.Click : num 9.63 8.61 37.66 13.59 6.8 ...
## $ Q67_Last.Click : num 40.4 29.1 53.2 55.2 22.2 ...
## $ Q67_Page.Submit : num 41.2 30 54.6 56.1 23.1 ...
## $ Q67_Click.Count : int 7 7 9 7 7 7 7 7 6 13 ...
## $ mindful_1 : int 4 2 2 2 4 1 5 3 3 5 ...
## $ mindful_2 : int 2 2 3 2 5 4 6 2 3 6 ...
## $ mindful_3 : int 2 2 1 1 3 3 5 4 4 4 ...
## $ mindful_4 : int 2 1 2 2 2 3 4 2 3 5 ...
## $ mindful_5 : int 4 3 3 2 4 5 6 2 3 6 ...
## [list output truncated]1.4 Subsetting Data
d <- subset(df, select=c(ResponseId,sex,race,
swb_1,
swb_2,
swb_3,
swb_4,
swb_5,
swb_6,
stress_1,
stress_2,
stress_3,
stress_4,
stress_5,
stress_6,
stress_7,
stress_8,
stress_9,
stress_10,
belong_1,
belong_2,
belong_3,
belong_4,
belong_5,
belong_6,
belong_7,
belong_8,
belong_9,
belong_10,
SocMedia_1,
SocMedia_2,
SocMedia_3,
SocMedia_4,
SocMedia_5,
SocMedia_6,
SocMedia_7,
SocMedia_8,
SocMedia_9,
SocMedia_10,
SocMedia_11))1.5 Basic Data Checking
1.5.1 Checking Values
d %>%
map(table, useNA = "always")## $ResponseId
##
## R_00aEuEBExladk8V R_00cbdktvaY86PbL R_02K0VTmup5OMJP3 R_06aTGiZAvuTngdP
## 1 1 1 1
## R_07h1OLlzcoZj7Q9 R_08MSceiScQuWWMV R_0AnPM5x7wfwX1bf R_0B4gtR1WbBTM34Z
## 1 1 1 1
## R_0BCnIHKONiN2fS1 R_0BRR4WuOgQsX7Zr R_0Cj1m8a7TIGCjwl R_0CJcqtXWnOo8uBz
## 1 1 1 1
## R_0cVogNKh17252Lf R_0DHawufGaevNITD R_0dHeG2u1sh8jBD3 R_0DJxVk198bJKW3L
## 1 1 1 1
## R_0dNdRm6ew3q0NTL R_0DO7VdrACYNGD4x R_0eSMVCDA6q7DlTP R_0f9Kp3Yh5d8dR17
## 1 1 1 1
## R_0fhBPYN8EIDum8J R_0fuW0LxSw8UBdNb R_0HfQhzNjRXj43oF R_0IhahecRrYVPWQZ
## 1 1 1 1
## R_0jkTKwF8erY09ed R_0jNsdXaoFwisOcx R_0k4hK2HpuEffOtb R_0NyXCCeAwrZy9MJ
## 1 1 1 1
## R_0OIVG4OddeIkBA9 R_0p0o20iOMuxc813 R_0pRBGCJnrZVUpM1 R_0PWnpufIzF3YIzT
## 1 1 1 1
## R_0q8r4AJ0KRqJD6F R_0qgwLO0x0MViDOp R_0SMFGU1spnVkY4Z R_0SSfg5WWjL2Pv2l
## 1 1 1 1
## R_0SWvon67Pp6xoad R_0U2icEWOOz0WnUl R_0U2W1vrCUsbD3Tv R_0Ujo9ij5Prw5p5z
## 1 1 1 1
## R_0uouoAArB6DgFZr R_0vtxu9tY1OZlZKh R_0wS0wVx2djmhoyx R_0xPHZrS6QJxGCaJ
## 1 1 1 1
## R_10AR1BhlKdqLzd9 R_10DzLeOYwIt65ES R_10GHdAruGK8PKsD R_10HtfDDQWAF0TUu
## 1 1 1 1
## R_10ID9IwsGTH8jKh R_10Iu1euwQG7u8Sd R_10o5g7NBIliz7y7 R_10OPyaWe3FGIg5T
## 1 1 1 1
## R_10osRVYQTozmPQz R_10OtPcHR8FRqYWc R_10OTSb3qKpsUpgY R_10PhoFvpHsSRUzq
## 1 1 1 1
## R_10qEDsOS2lof6ZX R_10qO2qYgU3X0g49 R_10qSpHLSgguQ3P4 R_10SGNtXcRPxkKPL
## 1 1 1 1
## R_10Ta8CCHcxAKrVv R_10TXsy91Zo8PPzr R_10u6G17JITY60xl R_10uS04Ubp4IwfYE
## 1 1 1 1
## R_10Uyk0IFlCgwSSS R_10wSj5XPe0tgJGz R_10Z9bVcmtG3o3nc R_10ZTeK5tAqSKyCl
## 1 1 1 1
## R_114KGbDvLZKVCnL R_114oIOatJSReBAv R_117TeYgqOVRfmSr R_11cg45iNm9C0EkE
## 1 1 1 1
## R_11gSRxVodM1SzNZ R_11gyCdnzpxAimFV R_11h0k4wkLXg6f3l R_11iS5uJleF16Vrt
## 1 1 1 1
## R_11XSc9UH9vYQpQd R_11Z2ipgG06JlwQh R_11ZRxisCLB5shIK R_120eAMA1JEaVzDg
## 1 1 1 1
## R_123cHWaIY9a7lTj R_125dBqVsrnXFXde R_125z5zdnETjS0jd R_126hlQCkLu4yrOw
## 1 1 1 1
## R_12As5dRrLv3frVH R_12DRYQVQXW9FAJy R_12F64OvWX2h8al3 R_12FkPYc6D6AmS8Z
## 1 1 1 1
## R_12fZ4Uf4AjC0nPp R_12G7bIqN2wB2N65 R_12G7i3IHX4oPbyX R_12hunWXMEYOKaOW
## 1 1 1 1
## R_12L1PtHgU43Acrq R_12L3kNuNIqjHsMr R_12LIvhyqfgiboWS R_12LQUiollwEFzsN
## 1 1 1 1
## R_12mbwWnjAW2oAZr R_12moVn7IJsErSy9 R_12QpuSszEB0ZXho R_12qZ4wj8OYFZoSe
## 1 1 1 1
## R_12r6sxr2ZFm7r0I R_12rUfK89ysLhGrV R_12rUozan444C5xF R_12RzALeawDdgvlj
## 1 1 1 1
## R_12sDTIswZPCWT2V R_12sxPUaUqY6MGUu R_12xKKUW6y5uX9p0 R_1AAIjIxYsrkDKF3
## 1 1 1 1
## R_1AOlcS2DxomEQbr R_1B2ErY9UgFeBC9n R_1Bae6Wt1u8czLot R_1BPIWXMM5sqx71l
## 1 1 1 1
## R_1BqeN645IHWLYBz R_1BQSJCdyKLabank R_1BW7rnVAPccRFkB R_1BWarcKJ0Gg3aO8
## 1 1 1 1
## R_1BWV7fsdyMARRcJ R_1C1lWtqTrdnwsl8 R_1C1vwGGStueiMsJ R_1C2g76yekBbh3Rr
## 1 1 1 1
## R_1C2gbqaQIESYVf3 R_1C42QZHqEWxKZXt R_1C8xsbJ9NbVPoyh R_1C8zOh7WDlKOW7N
## 1 1 1 1
## R_1CattXKeuxQvaJh R_1CBaRWVVRJHJfZU R_1CBnDZkcZPCwDdV R_1CE0KCrObpZDxGh
## 1 1 1 1
## R_1CEjf5qVtrqxbwJ R_1CEpgpuL7KJHYEi R_1CI43oP3J1ez8wR R_1CKJEq7siyO6EE5
## 1 1 1 1
## R_1Cl7ONhtvJCpssB R_1CpEVdduwKceHj2 R_1Cpudzi4IuG1xxq R_1cSoMVBYZtTafkJ
## 1 1 1 1
## R_1Csx16E3WHQdMlL R_1cUtktLa0HgUhDN R_1CvdMHOGrSUP42x R_1CvJ7B19kLK377K
## 1 1 1 1
## R_1CwInCbEYMvQx3V R_1CwkvKOZlYs2hfH R_1Cxx41ayuk0rrNb R_1CygJEsM94OqSPG
## 1 1 1 1
## R_1cZdNgSrtSiVSBl R_1cZGRsR5RpMDcIA R_1d44Xg1osep8cZM R_1d4vQ8U7vBSKLJh
## 1 1 1 1
## R_1d5MBBSjWY4FAnk R_1dAdQ4SKO3cCbl2 R_1DBFaq1IJwIxgKV R_1DBgHDRwoNqBoDW
## 1 1 1 1
## R_1DD8qsCXLvPOsuI R_1dEQbcs91OVCSCh R_1dF66xA0Q0neCpg R_1DFNnlVLJ9jjt8Y
## 1 1 1 1
## R_1dGlM4QYRqPAHUw R_1DHZxCSx0PEdq0i R_1DI2ba7koWlmmF0 R_1djp0B5WnReh6Dw
## 1 1 1 1
## R_1dLbD6qt7Whc9kD R_1DLINetRysy8CbS R_1DLJY2Olm6Adpbl R_1DLOJSE9D2PTGQr
## 1 1 1 1
## R_1dM5UPxM3Aba6E0 R_1dMFWARCMxaSuHd R_1dmMdKX9pcNamkb R_1dnKgkMNpCMkUZk
## 1 1 1 1
## R_1DNZvoLmuuExHjU R_1doDW54uiguPOi4 R_1dofwoAs8fbkdUl R_1DOy3jkqsqkJCgP
## 1 1 1 1
## R_1DpN3vHy4zBcf6I R_1DpOgFOzljFJPxH R_1DpSVgNK2WGepmU R_1DRRPakJVtTAalx
## 1 1 1 1
## R_1DRSsWhvzF4nsSa R_1ds2OpjJH90Kgk3 R_1dsDI3zBsKuHUD4 R_1DSFe3GjGeiuCkp
## 1 1 1 1
## R_1dshhiOR4EH7u1t R_1dtBAIcx9qOPEfy R_1DTINR2wS7YiYdr R_1DTKl5osv1GEvKv
## 1 1 1 1
## R_1DtWGmJQ734yfKx R_1Dtz1hwwfIyl22f R_1DU10SWcgZFbjXG R_1DuQkjLlXMzZJUg
## 1 1 1 1
## R_1DVgk1fLU9kPtmg R_1DvstcO4oEM43bF R_1DXNRpaCLK4adEc R_1DXYVEVPhR5tF2j
## 1 1 1 1
## R_1dy8DzF9od00vCL R_1DYF6fdTtLfPGT4 R_1dyoLztJ9flDhsK R_1DYxkI738N4dxAd
## 1 1 1 1
## R_1DzL2YSrjjlJgkk R_1E1goSmnUS3k0nU R_1E1hRiomdr9YcW3 R_1E4He93IpQWmcMq
## 1 1 1 1
## R_1E6GL9aJNI9DzUb R_1E6V08QyHtpTAFU R_1E6VtbRvOaIBQtd R_1E6XMtxrEO4wau4
## 1 1 1 1
## R_1EbQKNeegcIRuww R_1EcJDddZHddkUSR R_1eFadoRZYX8fZiS R_1eG19ADqnxyYVvm
## 1 1 1 1
## R_1EhgfyZuqzIJOPR R_1Ehqy1OHOZae7gG R_1EhuS7PEozygh5K R_1EhxwuV8dcx8nCY
## 1 1 1 1
## R_1EictPZzYdBaHgp R_1EiEtm2ZNl7dQHY R_1EihKePhUenEL9L R_1EimW1PHou5A3cS
## 1 1 1 1
## R_1eODPtY1LDc4aEN R_1eQOswa3suuc7pY R_1eqrAonjbqx7vxX R_1eRdanNNXfHV5TK
## 1 1 1 1
## R_1eRDkVMrVWovIEh R_1es3002vvYiH33q R_1eS6CWOUDS9wCsx R_1esjPnwrno36UUY
## 1 1 1 1
## R_1eUFa1WXhNDBVJK R_1eVH4Bc6yJCdcGn R_1ewVD7tcTWUmjzZ R_1EXs59TJEUsiMYW
## 1 1 1 1
## R_1exz3bknyDCeGzS R_1exZrxCtJfE2tGl R_1ey46oxQ0LGBtZe R_1f26SK42rIxx4tL
## 1 1 1 1
## R_1f2daygD74wsLAo R_1F3eLUtnUqenxLi R_1F3QzG0ZZzqHanH R_1F4keDKnGuApP5u
## 1 1 1 1
## R_1F4VD768SxNs4Rf R_1F5nrKQ29M6CCuo R_1F5uWdCFOIdF5WY R_1f8HIw0e9PPylrr
## 1 1 1 1
## R_1F8MvFpHIqkOysA R_1f9Fkx8HFLhhUaI R_1f9rkj303512Rx7 R_1FA4AioOjlWqsB6
## 1 1 1 1
## R_1FaoAqCUiqfAhwq R_1Fc3679aEemc305 R_1fdTIgxr4jeMPwG R_1FEBtEAKnHsa9GP
## 1 1 1 1
## R_1FEQ8xLWZeRoyqB R_1ff6IAASXqOv2IJ R_1FfcHLRPe8DXuQv R_1FFEr6YMK1zJPHe
## 1 1 1 1
## R_1FfVIhmrj3PdnzQ R_1Fglma4L378sP23 R_1Fh9c0RHPNan3VY R_1fjQVvavBUHCpPQ
## 1 1 1 1
## R_1fjY5WGwT4Ffaow R_1fkkdehLmm3RFdN R_1FQgPZ58XGYbtKq R_1FqP2f60qjz4S1C
## 1 1 1 1
## R_1FquPKcAqTJQzRl R_1FqUxVOZwUYcqvT R_1FRIvDGJw0IvJ7t R_1FUwtEwVNOh04Ux
## 1 1 1 1
## R_1FvEpRoEBuevUt3 R_1FzTcbiHVUsyUhM R_1g5DfwzFmfs5G8J R_1g89MwkzvujpyJm
## 1 1 1 1
## R_1g8B6UZlVVbib5g R_1g8uz0SSU0RgPdC R_1gAxha4oCC3u2bC R_1gbedjw2jC3aTOg
## 1 1 1 1
## R_1gBLu8cuzD7NKct R_1gcLcEFwIzfpWzp R_1GD1DpDmeqH8Kho R_1GDDvFFXIzLCy8s
## 1 1 1 1
## R_1geCLxV5a0s4afY R_1geEnXCe5qMGfZO R_1gel9SGPQpGqr8P R_1gGaOUjHPIINwJD
## 1 1 1 1
## R_1GHUmHNEnDpMar4 R_1GJ4eW8BxoZ3pte R_1gjA6dxe6FV4Yk6 R_1gjpw1fxApVBkcq
## 1 1 1 1
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## R_RfTmHpdulLopW9z R_RgxUfZFdXSerZV7 R_riiJjZ879Q1em8F R_rjcsRdDkFU5LcoV
## 1 1 1 1
## R_rje0xML6mcPbXax R_RjWpEAvlQ68XYFb R_rjYJvi9OIHWKiOt R_rk9JA9DSnFO80s9
## 1 1 1 1
## R_rkf1u33aHqkHGy5 R_rkzxn4KkNzgMWRP R_rl0eE7teuulFZU5 R_rls8Q5Sr57PiHh7
## 1 1 1 1
## R_RmJ3Jd3fBgsmoxz R_roKHBENfxrpHTZn R_roTXyW9xm0vaDBv R_RRF50cns0kqXuY9
## 1 1 1 1
## R_rrRQTWbKMr2G9fr R_RrSNupUJB6FNKmZ R_rrttZuiNvJz1D3P R_RrWZyJp3fMZulEJ
## 1 1 1 1
## R_RRyKQPYEIuH5rxv R_RspY7I8PDWHNiRb R_RWXSfCwGSTB5v0d R_RXmKE1fhB5sVYu5
## 1 1 1 1
## R_RzsmorXlKO4eoGR R_s5cpwgYPZxz2HwB R_s5wX18VCu98nlMR R_s6Gk0mY6dgsgPFn
## 1 1 1 1
## R_s6GlOpP1WJSh6oN R_s83qscBROEGLD6p R_sbvGtBjpbY4enCN R_sBZO4p4HjbmmASt
## 1 1 1 1
## R_scJR5aMnulg8yQh R_sCoXRY85aUpiGf7 R_sdJ4kmTgc08ajsd R_SDY9XhwDsN4NOed
## 1 1 1 1
## R_sGbMiZYCnTBXD9L R_shtqlVWdPrOuh8d R_shyncpd3VGLGyM9 R_SISk36cETkIezKh
## 1 1 1 1
## R_SIuZz0Ke1xupnvX R_SJn9b4riEW6cbqp R_sKXTaQN8ofK5Vzr R_sNhyckf10MG1sIx
## 1 1 1 1
## R_SNPTGLYE4O6SJtD R_sohbz6FSyA0w0SZ R_soIZEDHfgWRsX73 R_sOtJxiVoAJUDHZT
## 1 1 1 1
## R_sOwZCK2UG7jHHG1 R_SPh0iKrxFCo3p6h R_spsCbf0lO39qxmp R_sQXfDeC9CBGBfhv
## 1 1 1 1
## R_sQZvt8xr3XGCwXT R_sR0OOAlxyRIVjjj R_sRI8zDWH7X9Ivbr R_SSFWDWshbeTueS5
## 1 1 1 1
## R_sTHLVosHj4jYPmx R_sTrLUHjZowmvUDn R_sTYSKqCkoDk5OOR R_svwlmBGZE2vKTzX
## 1 1 1 1
## R_sySFV365cdiXbgt R_sz1qXSQQ6rVDDGh R_sZHkOxSQb6Msxb3 R_sZi2VtV3vcxIpPz
## 1 1 1 1
## R_sZjpTjX8CpRwXzX R_t0Ay3NtIEyan9TP R_T0CL0aIuAN3iCtP R_T0MI9WY3E2c6tkR
## 1 1 1 1
## R_T11ONpJ8DWTANA5 R_T1V4sUqO8mIWYOl R_T5Wdqoi0tdi9fLX R_T7B0VxgNivNji1P
## 1 1 1 1
## R_TckKoMAaKdnIHnz R_TdpUwVBj2gvWKuR R_tDqwAyc13bB8qRz R_TdUDIBb18UIgCgp
## 1 1 1 1
## R_tFEbTPyWjAKVkzL R_tGafKJlE6jc7TnX R_tGMUaYUREKRXd3H R_tGQz5XVbEXCUYaR
## 1 1 1 1
## R_tKRN7CtFIQqY8qB R_tLonsOXII9JFU09 R_tMvZqrlMZtpbWPT R_TnDBpK0zZ3qgtCF
## 1 1 1 1
## R_tRPFKdAV5oACxoJ R_TtnFEa68rSbSQiB R_TuAwlqvdn6YL6CZ R_tX8uoBHEsDUws9j
## 1 1 1 1
## R_u4SyE6Gm022bGpj R_u8604SCcGZen0yd R_u8nzto5sZMs7yoN R_u9A7Lpuc1R1VwNb
## 1 1 1 1
## R_Ua8rHkWD01EQhnX R_UaPcDZ7hCLzrKFP R_UapRCybZgVkQqNb R_UDCp582qhQSgOwF
## 1 1 1 1
## R_UEZykdV1BiavZG9 R_UFJofn4cAQbXnzz R_UgBHWFNN6KMvHCF R_UgRHuRkOg1iKdax
## 1 1 1 1
## R_UGU7BNbhfTxRH7H R_UgXGC2pm03oBQHv R_Ui5EEg1cOrONd1D R_UihzHe19xeVHFa9
## 1 1 1 1
## R_UJGIWndbnecA4cV R_UK3SOXcuKZBJ3ix R_UKiODuTDvxOlV7z R_UKrL3P70iccKwqR
## 1 1 1 1
## R_UL6BfBeLvCqDPDH R_UL9YToqfo4cUkRH R_ULJQBnBj4oDbtKx R_ulVLZnjX7Fzoout
## 1 1 1 1
## R_Umh7gdM7rk8SPJf R_umI8x8W3uqg4i1H R_UMUo41MhP9kL4GJ R_UMwpzUZEb35d9st
## 1 1 1 1
## R_UmXggVPg6xAGtvb R_UnC9VcijknhlpZv R_UniXPRjV2prZ0vD R_upPIwjCybhkGURb
## 1 1 1 1
## R_UQrDfjqqLSvZ5pD R_urkLUi8fdV4VzMd R_urnzs4hgmaq3fu9 R_USAjSSjwI1s6z5v
## 1 1 1 1
## R_Ut1qCmykaASH4WJ R_uvP3C9DUBZWP46B R_uwB9gPWPPijYH5v R_UXBq31PgA3jyh1f
## 1 1 1 1
## R_V22CAnrHihh9w8V R_V3GO8EX9v1CSu4h R_V3wsZf9dJhdu3fz R_V42Lx45G3Pf2kYV
## 1 1 1 1
## R_V4D8LV3EXOEHTbz R_vAYgUIIHNxtVkGJ R_vC4FtURnQmdSJbj R_vce5QHcFKQLqDtf
## 1 1 1 1
## R_vdeLWZW0nLoYJl7 R_vdgvyY8llNSDDEZ R_vdVCROJS4vLRUJz R_vdxBxWQmRSAhLXj
## 1 1 1 1
## R_vHX4vHKybfiI1jj R_vicsZ8Ejx3P4T05 R_vJlMJBV6y4VajjH R_VJxDonUVSEuQqvD
## 1 1 1 1
## R_VKaYd13vKutFeSZ R_vl4X3T2HwBPd7ax R_vMhsCGa1AGmgQ1z R_vMqbe00ginSC8md
## 1 1 1 1
## R_vP6LiGCEIKmK1cR R_VP7qtsSLSGgUnRv R_VPAHwtPP4h79ri1 R_VPbz3XSFJJVzfDb
## 1 1 1 1
## R_vpk0ZLeId9a33Ud R_vq421Bry1so6GU9 R_vqusUfIe7EnqWoV R_vqxmyWc8xtBdhex
## 1 1 1 1
## R_vrbvpCIPl98Ovu1 R_vrClbXaknWwcA6J R_vrGzouC5t8WSrC1 R_VRpqmK4Qyxsx6xz
## 1 1 1 1
## R_vubHWN2HmfxF85j R_vUpEiSySJBgzsT7 R_VUxUZP1EhUDzNRv R_vV2wMq8yEKDZDNf
## 1 1 1 1
## R_vvJoqvaCodMk8yR R_vw1GVn3jYIKrn7X R_vwdVwZEGDCydWI9 R_VWKgSLoAMBwfbC9
## 1 1 1 1
## R_vxac4k76uyIUt2x R_vxAiSahnhiOuH85 R_VXt7vrIJyBtiolX R_vZCnds9l4KSq1cl
## 1 1 1 1
## R_w0NzIzu6KXyqOBz R_w0qcNYgS9WUdI6l R_W1EGf2QJG0hn77H R_W25VncXfjvum6Up
## 1 1 1 1
## R_w4v6jEcK9Bnui3L R_w5BTS7ojQmTrRWp R_w5ebJR3z0EfKyAh R_W65Gs3Kc27pzxnz
## 1 1 1 1
## R_w6lxAMmtuX3Ek5X R_W6S35WYLHLscFVv R_W6TkEFYJpTlsl6V R_W6WIq7D3KkGS3MR
## 1 1 1 1
## R_W7O7KF7yEHPFdHH R_w7RcOnepWH2wOnT R_W8xMpW2yYzwS45r R_WBUWHjFN8VmL1sZ
## 1 1 1 1
## R_WcA58ouQdChPVTz R_WcEmFSCFvsfZ6XD R_WcyIKDc69mbiwWB R_WcZa6G916pFjJbr
## 1 1 1 1
## R_WDoTF7qZXCfkIbD R_WfEsejIkee3Colr R_WjGB1sKDJBfUDi9 R_WkbXsjnNFOBmO5P
## 1 1 1 1
## R_wL5G1eHIHJt4OE9 R_wLV8uVbwd9Hq0Ct R_wOks2PSuqruQOlj R_WpaxxZp37UO9I2d
## 1 1 1 1
## R_Wr1ZT9xEnPY0V9v R_wRi8WjZEQps2e2d R_wTrsTDnZuVudvep R_WuE77Tmkxe27VJv
## 1 1 1 1
## R_WuGSDCD5Bh7RBuh R_Wv9R6HdzTYHYS7T R_WvbXAzReYzy6IgN R_WvoppNlNMaJwOqJ
## 1 1 1 1
## R_WvwgSXdOAxjf9PX R_wYiU7404tbzVDe9 R_wZcI1elyiIBxsQ1 R_x0fEkXigXSx3YPf
## 1 1 1 1
## R_x2T1pZJRK5q3soF R_x4z9PgGtORz2bDP R_x5x2xw2KhvOjybT R_x9JFVQSWH2rwzYd
## 1 1 1 1
## R_x9tSJfHHlRPYeI1 R_xACwcdS3mhHmRYl R_xbfyhlLMvpvrs0F R_XESJAjmCh7d0obn
## 1 1 1 1
## R_xFbKsCdVWIBSl3z R_XgL6LNATJyhxjTH R_xgrhw19BNeutEvT R_XGrxUS1XcfXxA65
## 1 1 1 1
## R_xgXu2pj6z8Z47El R_XHdyMaik28PToVH R_xinAHaGX73o2ak1 R_XKYWl0uR6LXbwKR
## 1 1 1 1
## R_xlQVDXU3WHKlDfX R_XLZduf1UmcI3dTz R_XM6PgM5UBmZGFzP R_XNx5Ihc9npOoyKB
## 1 1 1 1
## R_XpvMtq8GyXne6tj R_Xqed5qjTP5W3NPb R_xr45aVFqM3Bj6EN R_xryJBM8NY8bAlZD
## 1 1 1 1
## R_XSu8wjE68V9OJEd R_xsUHjhOPeQdEybf R_XTCu6Anhjie1wJj R_XTESNoCsrsfb35T
## 1 1 1 1
## R_XTIAIAIwSt3pSBX R_XtPD6eArGbEnECl R_XtUdI9TpyP1tKAp R_xuDczhEtyooS45X
## 1 1 1 1
## R_XUrkCVzaWN7qSuR R_xuupGEX4vq6A91L R_Xvopl0UvSmAhHrz R_XvTh7edKJftNE4h
## 1 1 1 1
## R_Xwe7JaGKKFYDyRb R_XwhXfHx4EmfiBWh R_Xwi9eReJDcSEZ21 R_xyBn828HK6VyBZT
## 1 1 1 1
## R_xyCNZJ4IykKu8Gl R_xykCZZdnteyZF1T R_XYyvbarNtY0wueR R_xzISJ4ujcslhKEx
## 1 1 1 1
## R_xzp39EAu9iscVW1 R_xzRLqbGz6pe4oX7 R_XzSvdxyrgLSdpXb R_xzTFQ1FmDDQ4wfL
## 1 1 1 1
## R_Y3SKThqEBz6Jjd7 R_Y69XOURBCDXZd0R R_Y91QtI6V8NcgUEx R_YbFSLhmurtOWZJ7
## 1 1 1 1
## R_yCtUbug4qskv83L R_yEjcQBFx9pdSutj R_yjs5RFwSVqGDFhD R_ylrlUzwFzk6D0L7
## 1 1 1 1
## R_ymyvzdaHBIdanpD R_yOb3NwdQ0B8ZBfz R_yOr8H3Xq0bJ3BGV R_yP9ZidBGyFTJmY9
## 1 1 1 1
## R_ypFhvhYUSnjMvex R_yPg2lwzLLvdyRKV R_yqm9uvxabaX1AiZ R_yR612aOKU7sQFih
## 1 1 1 1
## R_yrOn3isgHdPPRAd R_yrq35WjNwdZD4Ix R_yrwZmYEtRe4NycF R_yUqMuFeWrmCoGgF
## 1 1 1 1
## R_YVRsM1SqLTXKZdn R_YVtQ1gDJoao90Ax R_YW8RDLOru3UB5Gp R_ywki5fArUkja91f
## 1 1 1 1
## R_ywqkLvP8SOCmVPz R_yWxpDHDRHE8j7cB R_yx7CYfp2lJbkfmh R_yXdevlGkmVvTG0h
## 1 1 1 1
## R_YXiLIxboMOeLF6h R_YXlkszpOYeSMqQN R_yym10RKiHtU4OJz R_z07k9TQvgpqxnJn
## 1 1 1 1
## R_Z2m4cF3KzhZ2VFv R_Z3FsWrOdrY35khr R_Z8ofSdLse5DeUHD R_z8SXE7RpMWrIOFb
## 1 1 1 1
## R_Za7CjBkxnCNkOiZ R_ZCDOpJHsJiTFiRb R_zdsbKsrHU1kq99L R_zdwzrMmBEVqs5pf
## 1 1 1 1
## R_ZDzzdUEtdg609Fv R_zeapSz3oRBGLfGx R_zeQs23FAQQ9Cy3L R_zeVzInz0dHCKY6t
## 1 1 1 1
## R_zeWrXx8kySc3FCh R_ZFe6soTVT0aGw9j R_zfiAXwOzjsI5ZkJ R_ZgTI5GweP98aBot
## 1 1 1 1
## R_ZkGG5UUVfc1I3MR R_ZLcXEENfgpCWEIp R_Zm13o5i8d4Z4mv7 R_ZpEp1PVdm66wrWV
## 1 1 1 1
## R_ZqrZHpaqfrgPhlL R_Zr6Xylj6BTWq5xf R_ZrApYB5flld5sBz R_ZrD49jng3sxz2W5
## 1 1 1 1
## R_ZsHquDajFMklhId R_zSUlFa0qHFGio9j R_zTIWeOowIY0VPQR R_Zx9FTPo9AtmNN3r
## 1 1 1 1
## R_zYCEZx56Qlj1ytX R_ZymeVsrbugX4jPr <NA>
## 1 1 0
##
## $sex
##
## 1 2 3 <NA>
## 792 2332 54 4
##
## $race
##
## 1 1,2 1,2,3 1,2,3,4,5 1,2,3,5 1,2,4 1,2,4,5
## 9 2026 26 2 1 3 4 3
## 1,2,5 1,2,6 1,3 1,3,4 1,3,5 1,4 1,4,5 1,5
## 4 2 98 6 8 39 2 35
## 1,6 2 2,3 2,3,4 2,3,4,5 2,3,5 2,3,6 2,4
## 15 249 5 1 1 1 1 6
## 2,5 2,5,6 2,6 3 3,4 3,4,5 3,5 4
## 5 1 6 286 9 1 5 210
## 4,6 5 6 <NA>
## 3 12 97 0
##
## $swb_1
##
## 1 2 3 4 5 6 7 <NA>
## 234 408 449 467 788 617 215 4
##
## $swb_2
##
## 1 2 3 4 5 6 7 <NA>
## 108 243 382 458 782 812 394 3
##
## $swb_3
##
## 1 2 3 4 5 6 7 <NA>
## 125 200 332 375 767 993 386 4
##
## $swb_4
##
## 1 2 3 4 5 6 7 <NA>
## 137 285 351 416 847 805 337 4
##
## $swb_5
##
## 1 2 3 4 5 6 7 <NA>
## 374 489 597 318 506 567 327 4
##
## $swb_6
##
## 1 2 3 4 5 6 7 <NA>
## 255 394 407 416 730 678 298 4
##
## $stress_1
##
## 1 2 3 4 5 <NA>
## 147 656 1331 775 268 5
##
## $stress_2
##
## 1 2 3 4 5 <NA>
## 209 665 1074 786 443 5
##
## $stress_3
##
## 1 2 3 4 5 <NA>
## 31 128 639 1037 1342 5
##
## $stress_4
##
## 1 2 3 4 5 <NA>
## 68 359 1217 1098 434 6
##
## $stress_5
##
## 1 2 3 4 5 <NA>
## 119 523 1482 857 196 5
##
## $stress_6
##
## 1 2 3 4 5 <NA>
## 221 826 1164 662 304 5
##
## $stress_7
##
## 1 2 3 4 5 <NA>
## 99 461 1395 1007 215 5
##
## $stress_8
##
## 1 2 3 4 5 <NA>
## 135 572 1340 948 181 6
##
## $stress_9
##
## 1 2 3 4 5 <NA>
## 175 646 1123 846 387 5
##
## $stress_10
##
## 1 2 3 4 5 <NA>
## 295 763 1037 660 422 5
##
## $belong_1
##
## 1 2 3 4 5 <NA>
## 225 841 626 981 505 4
##
## $belong_2
##
## 1 2 3 4 5 <NA>
## 276 562 727 1080 533 4
##
## $belong_3
##
## 1 2 3 4 5 <NA>
## 413 939 672 848 306 4
##
## $belong_4
##
## 1 2 3 4 5 <NA>
## 91 188 321 1217 1362 3
##
## $belong_5
##
## 1 2 3 4 5 <NA>
## 132 200 636 1390 821 3
##
## $belong_6
##
## 1 2 3 4 5 <NA>
## 381 720 800 738 540 3
##
## $belong_7
##
## 1 2 3 4 5 <NA>
## 428 942 580 809 418 5
##
## $belong_8
##
## 1 2 3 4 5 <NA>
## 266 558 743 1081 530 4
##
## $belong_9
##
## 1 2 3 4 5 <NA>
## 279 572 730 1164 433 4
##
## $belong_10
##
## 1 2 3 4 5 <NA>
## 410 760 637 939 431 5
##
## $SocMedia_1
##
## 1 2 3 4 5 <NA>
## 302 599 1136 833 308 4
##
## $SocMedia_2
##
## 1 2 3 4 5 <NA>
## 581 832 820 662 284 3
##
## $SocMedia_3
##
## 1 2 3 4 5 <NA>
## 148 298 808 1164 761 3
##
## $SocMedia_4
##
## 1 2 3 4 5 <NA>
## 348 638 830 880 483 3
##
## $SocMedia_5
##
## 1 2 3 4 5 <NA>
## 386 910 1032 602 249 3
##
## $SocMedia_6
##
## 1 2 3 4 5 <NA>
## 267 371 820 1042 679 3
##
## $SocMedia_7
##
## 1 2 3 4 5 <NA>
## 318 433 816 956 654 5
##
## $SocMedia_8
##
## 1 2 3 4 5 <NA>
## 892 978 684 414 210 4
##
## $SocMedia_9
##
## 1 2 3 4 5 <NA>
## 414 669 1009 776 310 4
##
## $SocMedia_10
##
## 1 2 3 4 5 <NA>
## 188 323 879 1116 673 3
##
## $SocMedia_11
##
## 1 2 3 4 5 <NA>
## 313 572 914 871 509 31.6 Recoding Variables
table(d$sex, useNA = "always")##
## 1 2 3 <NA>
## 792 2332 54 4d$gender[d$sex == "1"] <- "m"
d$gender[d$sex == "2"] <- "f"
d$gender[d$sex == "3"] <- "nb"
table(d$gender, useNA = "always")##
## f m nb <NA>
## 2332 792 54 4table(d$race, useNA = "always")##
## 1 1,2 1,2,3 1,2,3,4,5 1,2,3,5 1,2,4 1,2,4,5
## 9 2026 26 2 1 3 4 3
## 1,2,5 1,2,6 1,3 1,3,4 1,3,5 1,4 1,4,5 1,5
## 4 2 98 6 8 39 2 35
## 1,6 2 2,3 2,3,4 2,3,4,5 2,3,5 2,3,6 2,4
## 15 249 5 1 1 1 1 6
## 2,5 2,5,6 2,6 3 3,4 3,4,5 3,5 4
## 5 1 6 286 9 1 5 210
## 4,6 5 6 <NA>
## 3 12 97 0d$race_rc <- NA
d$race_rc[df$race == 1] <- "white"
d$race_rc[df$race == 2] <- "black"
d$race_rc[df$race == 3] <- "hispanic"
d$race_rc[df$race == 4] <- "asian"
d$race_rc[df$race == 5] <- "nativeamer"
d$race_rc[df$race == 6] <- "other"
d$race_rc[grep(",", d$race)] <- "multiracial"
table(d$race_rc, useNA = "always")##
## asian black hispanic multiracial nativeamer other
## 210 249 286 293 12 97
## white <NA>
## 2026 91.7 Factor Scores/Composite Variables
d$swb <- (d$swb_1 +
d$swb_2 +
d$swb_3 +
d$swb_4 +
d$swb_5 +
d$swb_6)/6
d$stress <- (d$stress_1 +
d$stress_2 +
d$stress_3 +
d$stress_4 +
d$stress_5 +
d$stress_6 +
d$stress_7 +
d$stress_8 +
d$stress_9 +
d$stress_10)/10
d$belong <- (d$belong_1 +
d$belong_2 +
d$belong_3 +
d$belong_4 +
d$belong_5 +
d$belong_6 +
d$belong_7 +
d$belong_8 +
d$belong_9 +
d$belong_10)/10
d$SocMedia <- (d$SocMedia_1 +
d$SocMedia_2 +
d$SocMedia_3 +
d$SocMedia_4 +
d$SocMedia_5 +
d$SocMedia_6 +
d$SocMedia_7 +
d$SocMedia_8 +
d$SocMedia_9 +
d$SocMedia_10 +
d$SocMedia_11)/111.8 Exporting Data
d2 <- subset(d, select=c(ResponseId, gender, race_rc, swb, stress, belong, SocMedia))
write.csv(d2, file="eammi2_final.csv", row.names = F)2 Basic Statistics
2.1 Import Cleaned Data
d <- read.csv(file="eammi2_final.csv", header=T)2.1.1 Load Libraries
library(tidyverse) # for the map() command
library(psych) # for the describe() command##
## Attaching package: 'psych'## The following objects are masked from 'package:ggplot2':
##
## %+%, alphalibrary(naniar) # for the gg_miss-upset() command
library(expss) # for the cross_cases() command## Loading required package: maditr##
## To select columns from data: columns(mtcars, mpg, vs:carb)##
## Attaching package: 'maditr'## The following objects are masked from 'package:dplyr':
##
## between, coalesce, first, last## The following object is masked from 'package:purrr':
##
## transpose## The following object is masked from 'package:readr':
##
## cols##
## Use 'expss_output_rnotebook()' to display tables inside R Notebooks.
## To return to the console output, use 'expss_output_default()'.##
## Attaching package: 'expss'## The following object is masked from 'package:naniar':
##
## is_na## The following objects are masked from 'package:stringr':
##
## fixed, regex## The following objects are masked from 'package:dplyr':
##
## compute, contains, na_if, recode, vars, where## The following objects are masked from 'package:purrr':
##
## keep, modify, modify_if, when## The following objects are masked from 'package:tidyr':
##
## contains, nest## The following object is masked from 'package:ggplot2':
##
## vars2.2 Check Data
2.2.1 Formatting
str(d)## 'data.frame': 3182 obs. of 7 variables:
## $ ResponseId: chr "R_BJN3bQqi1zUMid3" "R_2TGbiBXmAtxywsD" "R_12G7bIqN2wB2N65" "R_39pldNoon8CePfP" ...
## $ gender : chr "f" "m" "m" "f" ...
## $ race_rc : chr "white" "white" "white" "other" ...
## $ swb : num 4.33 4.17 1.83 5.17 3.67 ...
## $ stress : num 3.3 3.6 3.3 3.2 3.5 2.9 3.2 3 2.9 3.2 ...
## $ belong : num 3.4 3.4 3.6 3.6 3.2 3.4 3.5 3.2 3.5 2.7 ...
## $ SocMedia : num 4.27 2.09 3.09 3.18 3.36 ...d$ResponseId <- as.factor(d$ResponseId)
d$race_rc <- as.factor(d$race_rc)
d$gender <- as.factor(d$gender)2.2.2 Univariate Normality
describe(d)## vars n mean sd median trimmed mad min max range
## ResponseId* 1 3182 1591.50 918.71 1591.50 1591.50 1179.41 1 3182 3181
## gender* 2 3178 1.28 0.49 1.00 1.21 0.00 1 3 2
## race_rc* 3 3173 5.53 2.13 7.00 5.88 0.00 1 7 6
## swb 4 3178 4.47 1.32 4.67 4.53 1.48 1 7 6
## stress 5 3175 3.27 0.41 3.30 3.26 0.44 1 5 4
## belong 6 3175 3.31 0.49 3.30 3.33 0.44 1 5 4
## SocMedia 7 3175 3.13 0.78 3.18 3.16 0.67 1 5 4
## skew kurtosis se
## ResponseId* 0.00 -1.20 16.29
## gender* 1.40 0.88 0.01
## race_rc* -0.98 -0.68 0.04
## swb -0.36 -0.46 0.02
## stress -0.16 2.67 0.01
## belong -0.33 0.64 0.01
## SocMedia -0.31 0.26 0.012.2.3 Histograms
hist(d$swb)
hist(d$stress)
hist(d$belong)
table(d$race_rc, useNA = "always")##
## asian black hispanic multiracial nativeamer other
## 210 249 286 293 12 97
## white <NA>
## 2026 9table(d$gender, useNA = "always")##
## f m nb <NA>
## 2332 792 54 42.3 Missing Data
gg_miss_upset(d, nsets = 6)
d2 <- na.omit(d)2.4 Crosstabs & Scatterplots
2.4.1 Crosstabs
cross_cases(d2, race_rc, gender)|  gender | |||
|---|---|---|---|
|  f |  m |  nb | |
|  race_rc | |||
|    asian | 149 | 57 | 1 |
|    black | 181 | 63 | 2 |
|    hispanic | 207 | 76 | 2 |
|    multiracial | 222 | 61 | 10 |
|    nativeamer | 11 | 1 | |
|    other | 72 | 24 | 1 |
|    white | 1475 | 506 | 38 |
|    #Total cases | 2317 | 788 | 54 |
2.4.2 Scatterplots
plot(d2$swb, d2$stress,
main="Scatterplot of Subjective Well-Being and Stress",
xlab = "Swb Score",
ylab = "Stress Score")
plot(d2$swb, d2$belong,
main="Scatterplot of Subjective Well-Being and Need to Belong",
xlab = "Swb Score",
ylab = "Belong Score")
plot(d2$swb, d2$SocMedia,
main="Scatterplot of Subjective Well-Being and Social Media Use",
xlab = "Swb Score",
ylab = "SocMedia Score")
plot(d2$belong, d2$SocMedia,
main="Scatterplot of Need to Belong and Social Media Use",
xlab = "Belong Score",
ylab = "SocMedia Score")
plot(d2$stress, d2$SocMedia,
main="Scatterplot of Stress and Social Media Use",
xlab = "Stress Score",
ylab = "SocMedia Score")
plot(d2$belong, d2$stress,
main="Scatterplot of Need to Belong and Stress",
xlab = "Belong Score",
ylab = "Stress Score")
2.4.3 Boxplots
boxplot(data=d2, belong~race_rc,
main="Boxplot of Need to Belong and Participant Race",
xlab = "Participant Race",
ylab = "Belong Score")
boxplot(data=d2, SocMedia~gender,
main="Boxplot of Social Media Use and Sex",
xlab = "Participant Sex",
ylab = "Social Media Use")
3 Homework Writeup
Do your continuous variables meet the criteria for univariate normality? Skew and kurtosis should be between -2 and +2.
Yes, my continuous variables meet this criteria.
Subjective Well-Being (swb) : skew = -0.36, kurtosis = -0.46
Stress : skew = -0.16, kurtosis = 2.67
Need to Belong (belong) : skew = -0.33, kurtosis = 0.64
Social Media Use (SocMedia) : skew = -0.31, kurtosis = 0.26
Do you have any missing data? Once you have removed the cases/participants with missing data, what is your total sample size? Please discuss how much data is missing and whether it’s due to survey design or individual non-response.
I do have missing data. 18 participants did not see some of the survey questions due to how the the survey was designed (unit non response). 5 participants skipped some of the items selected for analysis (item nonresponse). After removing the participants with missing data my sample was 3159.