Ankita(488745)
2026-02-04
1. Data Source
The analysis uses data from the European Social Survey (ESS),
Round 11.
The ESS is a cross-national survey covering a wide range of European
countries, allowing for broad geographical representation.
The integrated ESS dataset ensures consistency across countries and
variables. ## 2. Objective of the Analysis
The objective of this analysis is to explore patterns
associated with individuals’ perceptions of their household
income.
Specifically, association rule mining is applied with:
Feeling about household’s income nowadays
(hincfel) as the rule consequent.
This allows identification of socio-demographic and well-being characteristics that are frequently associated with different income perceptions.
library(dplyr)
library(stringr)
library(arules)
library(ggplot2)
library(tidyr)
library(arulesViz)Load ESS Round
ess=read.csv("ESS11e04_1.csv")head(ess)## name essround edition proddate idno cntry dweight pspwght
## 1 ESS11e04_1 11 4.1 12.01.2026 50014 AT 1.1851145 0.3928906
## 2 ESS11e04_1 11 4.1 12.01.2026 50030 AT 0.6098981 0.3251533
## 3 ESS11e04_1 11 4.1 12.01.2026 50057 AT 1.3923296 4.0000234
## 4 ESS11e04_1 11 4.1 12.01.2026 50106 AT 0.5560615 0.1762276
## 5 ESS11e04_1 11 4.1 12.01.2026 50145 AT 0.7227953 1.0609399
## 6 ESS11e04_1 11 4.1 12.01.2026 50158 AT 0.9926053 1.3928125
## pweight anweight nwspol netusoft netustm ppltrst pplfair pplhlp polintr
## 1 0.3309145 0.13001321 90 5 180 5 5 5 1
## 2 0.3309145 0.10759795 90 5 570 10 0 1 2
## 3 0.3309145 1.32366590 30 5 30 6 9 8 2
## 4 0.3309145 0.05831629 15 1 6666 6 6 6 3
## 5 0.3309145 0.35108042 60 5 120 6 3 8 2
## 6 0.3309145 0.46090190 120 5 120 8 8 4 2
## psppsgva actrolga psppipla cptppola trstprl trstlgl trstplc trstplt trstprt
## 1 4 5 4 5 6 9 10 5 5
## 2 3 2 3 2 6 6 4 1 0
## 3 4 4 4 3 7 5 8 4 4
## 4 2 2 2 3 5 6 9 3 3
## 5 3 1 4 3 6 8 8 5 5
## 6 2 3 2 3 3 5 7 5 5
## trstep trstun vote prtvtdat prtvtebe prtvtfbg prtvtchr prtvtccy prtvtiee
## 1 5 5 1 1 NA NA NA NA NA
## 2 5 5 1 5 NA NA NA NA NA
## 3 7 5 1 5 NA NA NA NA NA
## 4 4 4 2 66 NA NA NA NA NA
## 5 6 8 1 5 NA NA NA NA NA
## 6 4 6 1 7 NA NA NA NA NA
## prtvtffi prtvtffr prtvgde1 prtvgde2 prtvtegr prtvthhu prtvteis prtvteie
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## prtvteil prtvteit prtvtblv prtvclt1 prtvclt2 prtvclt3 prtvtbme prtvtinl
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## prtvtcno prtvtfpl prtvtept prtvtbrs prtvtesk prtvtgsi prtvtges prtvtese
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## prtvthch prtvtdua prtvtdgb contplt donprty badge sgnptit pbldmna bctprd
## 1 NA NA NA 2 2 2 2 2 2
## 2 NA NA NA 2 2 1 1 1 1
## 3 NA NA NA 1 1 2 1 1 1
## 4 NA NA NA 2 2 2 2 2 2
## 5 NA NA NA 2 2 2 1 2 2
## 6 NA NA NA 2 2 2 2 2 1
## pstplonl volunfp clsprty prtcleat prtclebe prtclfbg prtclbhr prtclccy
## 1 2 2 1 1 NA NA NA NA
## 2 2 1 1 5 NA NA NA NA
## 3 1 1 1 5 NA NA NA NA
## 4 2 2 2 66 NA NA NA NA
## 5 2 2 1 5 NA NA NA NA
## 6 2 2 2 66 NA NA NA NA
## prtcliee prtclgfi prtclgfr prtclgde prtclegr prtclihu prtcleis prtclfie
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## prtclfil prtclfit prtclblv prtclclt prtclbme prtclhnl prtclcno prtcljpl
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## prtclgpt prtclbrs prtclesk prtclgsi prtclhes prtclese prtclhch prtcleua
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## prtcldgb prtdgcl lrscale stflife stfeco stfgov stfdem stfedu stfhlth gincdif
## 1 NA 2 5 8 6 4 6 8 8 2
## 2 NA 2 0 9 2 5 7 10 10 1
## 3 NA 2 3 10 6 5 6 5 8 1
## 4 NA 6 5 7 4 4 6 5 2 1
## 5 NA 2 2 9 6 7 8 9 9 2
## 6 NA 6 4 8 4 2 3 3 7 2
## freehms hmsfmlsh hmsacld euftf lrnobed loylead imsmetn imdfetn impcntr
## 1 2 4 3 6 4 4 2 2 3
## 2 1 5 1 9 2 5 2 2 2
## 3 1 5 1 7 5 3 1 1 1
## 4 2 4 3 5 2 9 2 2 2
## 5 2 4 2 10 1 2 1 1 2
## 6 2 4 2 3 2 2 2 3 3
## imbgeco imueclt imwbcnt happy sclmeet inprdsc sclact crmvct aesfdrk health
## 1 7 3 5 8 4 1 3 2 2 3
## 2 6 5 9 9 7 4 4 1 3 2
## 3 9 9 8 9 4 4 3 2 3 1
## 4 6 6 5 7 6 3 3 2 3 3
## 5 10 10 10 9 5 4 3 2 1 2
## 6 5 6 6 8 6 4 2 2 2 1
## hlthhmp atchctr atcherp rlgblg rlgdnm rlgdnbat rlgdncy rlgdnafi rlgdnade
## 1 3 10 5 1 1 1 NA NA NA
## 2 2 8 8 2 66 6666 NA NA NA
## 3 3 9 7 2 66 6666 NA NA NA
## 4 3 10 8 1 3 10 NA NA NA
## 5 3 10 10 1 1 1 NA NA NA
## 6 3 8 6 1 1 1 NA NA NA
## rlgdnagr rlgdnhu rlgdnais rlgdnie rlgdnlv rlgdnlt rlgdme rlgdnanl rlgdnno
## 1 NA NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA NA
## rlgdnapl rlgdnapt rlgdnrs rlgdnask rlgdnase rlgdnach rlgdnaua rlgdngb rlgblge
## 1 NA NA NA NA NA NA NA NA 6
## 2 NA NA NA NA NA NA NA NA 2
## 3 NA NA NA NA NA NA NA NA 1
## 4 NA NA NA NA NA NA NA NA 6
## 5 NA NA NA NA NA NA NA NA 6
## 6 NA NA NA NA NA NA NA NA 6
## rlgdnme rlgdebat rlgdecy rlgdeafi rlgdeade rlgdeagr rlgdehu rlgdeais rlgdeie
## 1 66 6666 NA NA NA NA NA NA NA
## 2 66 6666 NA NA NA NA NA NA NA
## 3 1 1 NA NA NA NA NA NA NA
## 4 66 6666 NA NA NA NA NA NA NA
## 5 66 6666 NA NA NA NA NA NA NA
## 6 66 6666 NA NA NA NA NA NA NA
## rlgdelv rlgdelt rlgdeme rlgdeanl rlgdeno rlgdeapl rlgdeapt rlgders rlgdeask
## 1 NA NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA NA
## rlgdease rlgdeach rlgdeaua rlgdegb rlgdgr rlgatnd pray dscrgrp dscrrce
## 1 NA NA NA NA 5 6 5 2 0
## 2 NA NA NA NA 0 7 6 2 0
## 3 NA NA NA NA 8 5 3 1 0
## 4 NA NA NA NA 6 6 3 2 0
## 5 NA NA NA NA 1 7 7 2 0
## 6 NA NA NA NA 3 5 1 2 0
## dscrntn dscrrlg dscrlng dscretn dscrage dscrgnd dscrsex dscrdsb dscroth
## 1 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 1 0 0 0
## 4 0 0 0 0 0 0 0 0 0
## 5 0 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0 0
## dscrdk dscrref dscrnap dscrna ctzcntr brncntr cntbrthd livecnta lnghom1
## 1 0 0 1 0 1 1 6666 6666 GER
## 2 0 0 1 0 1 1 6666 6666 GER
## 3 0 0 0 0 1 1 6666 6666 GER
## 4 0 0 1 0 2 2 RO 1989 GER
## 5 0 0 1 0 1 1 6666 6666 GER
## 6 0 0 1 0 1 2 CZ 1965 GER
## lnghom2 feethngr facntr fbrncntc mocntr mbrncntc ccnthum ccrdprs wrclmch
## 1 000 1 1 6666 1 6666 4 4 4
## 2 ENG 8 1 6666 1 6666 3 10 5
## 3 ENG 1 1 6666 1 6666 4 8 5
## 4 RUM 2 2 RO 2 RO 4 6 4
## 5 000 1 1 6666 1 6666 5 10 4
## 6 ENG 1 2 CZ 2 CZ 5 8 4
## admrclc testjc34 testjc35 testjc36 testjc37 testjc38 testjc39 testjc40
## 1 2 66 66 66 2 2 3 6
## 2 3 66 66 66 6 6 6 3
## 3 2 66 66 66 3 4 3 6
## 4 2 66 66 66 4 4 4 6
## 5 3 66 66 66 6 6 6 4
## 6 3 66 66 66 6 6 6 3
## testjc41 testjc42 vteurmmb vteubcmb ctrlife etfruit eatveg dosprt cgtsmok
## 1 6 6 1 NA 8 3 3 3 4
## 2 3 2 55 NA 8 1 1 5 5
## 3 6 6 1 NA 9 4 3 3 1
## 4 6 6 55 NA 8 2 2 3 6
## 5 2 1 1 NA 9 3 3 3 1
## 6 2 0 1 NA 8 5 3 4 5
## alcfreq alcwkdy alcwknd icgndra alcbnge height weighta dshltgp dshltms
## 1 3 20.0 21.6 1 5 178 90 1 1
## 2 3 70.4 64.0 2 2 168 74 1 0
## 3 4 72.0 72.0 2 5 180 95 1 1
## 4 7 6666.0 6666.0 6 6 167 70 1 1
## 5 2 24.0 48.0 2 4 168 67 0 1
## 6 2 24.0 24.0 2 2 155 60 1 1
## dshltnt dshltref dshltdk dshltna medtrun medtrnp medtrnt medtroc medtrnl
## 1 0 0 0 0 2 0 0 0 0
## 2 0 0 0 0 2 0 0 0 0
## 3 0 0 0 0 2 0 0 0 0
## 4 0 0 0 0 2 0 0 0 0
## 5 0 0 0 0 2 0 0 0 0
## 6 0 0 0 0 2 0 0 0 0
## medtrwl medtrnaa medtroth medtrnap medtrref medtrdk medtrna medtrnu hlpfmly
## 1 0 0 0 1 0 0 0 1 2
## 2 0 0 0 1 0 0 0 2 1
## 3 0 0 0 1 0 0 0 1 1
## 4 0 0 0 1 0 0 0 1 2
## 5 0 0 0 1 0 0 0 1 2
## 6 0 0 0 1 0 0 0 1 1
## hlpfmhr trhltacu trhltacp trhltcm trhltch trhltos trhltho trhltht trhlthy
## 1 66 0 0 0 0 0 0 0 0
## 2 2 0 0 0 0 0 0 0 0
## 3 1 0 0 1 0 0 0 0 0
## 4 66 0 0 0 0 0 0 0 0
## 5 66 0 0 0 0 0 1 1 0
## 6 1 0 0 0 0 0 0 1 0
## trhltmt trhltpt trhltre trhltsh trhltnt trhltref trhltdk trhltna fltdpr
## 1 0 0 0 0 1 0 0 0 1
## 2 0 0 0 0 1 0 0 0 2
## 3 0 0 0 0 0 0 0 0 2
## 4 0 0 0 0 1 0 0 0 2
## 5 0 0 0 0 0 0 0 0 1
## 6 1 1 0 0 0 0 0 0 1
## flteeff slprl wrhpp fltlnl enjlf fltsd cldgng hltprhc hltprhb hltprbp hltpral
## 1 1 1 3 1 3 1 1 0 1 0 0
## 2 2 3 3 3 4 2 2 1 0 0 0
## 3 2 3 3 1 3 1 2 0 0 0 0
## 4 2 3 2 2 2 2 2 0 1 0 0
## 5 1 1 3 1 3 1 1 0 0 0 0
## 6 2 2 4 1 4 1 2 0 1 0 0
## hltprbn hltprpa hltprpf hltprsd hltprsc hltprsh hltprdi hltprnt hltprref
## 1 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0
## 3 0 0 1 0 0 0 0 0 0
## 4 1 0 0 0 0 0 1 0 0
## 5 0 0 0 0 0 0 0 1 0
## 6 0 0 0 1 0 0 0 0 0
## hltprdk hltprna hltphhc hltphhb hltphbp hltphal hltphbn hltphpa hltphpf
## 1 0 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 1 1
## 4 0 0 0 0 0 0 1 0 0
## 5 0 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0 0
## hltphsd hltphsc hltphsh hltphdi hltphnt hltphnap hltphref hltphdk hltphna
## 1 0 0 0 0 1 0 0 0 0
## 2 0 0 0 0 0 0 1 0 0
## 3 0 0 0 0 0 0 0 0 0
## 4 0 0 0 1 0 0 0 0 0
## 5 0 0 0 0 0 1 0 0 0
## 6 0 0 0 0 1 0 0 0 0
## hltprca cancfre cnfpplh fnsdfml jbexpvi jbexpti jbexpml jbexpmc jbexpnt
## 1 3 6 4 5 0 0 0 0 0
## 2 3 6 2 4 0 0 0 0 1
## 3 3 6 4 2 0 0 0 0 1
## 4 3 6 4 3 0 1 1 0 0
## 5 3 6 5 5 0 0 0 0 1
## 6 3 6 4 4 0 0 0 0 1
## jbexpnap jbexpref jbexpdk jbexpna jbexevl jbexevh jbexevc jbexera jbexecp
## 1 1 0 0 0 0 0 0 0 0
## 2 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 0 0 0
## 4 0 0 0 0 0 0 0 0 1
## 5 0 0 0 0 0 0 0 0 0
## 6 0 0 0 0 0 0 0 0 0
## jbexebs jbexent jbexenap jbexeref jbexedk jbexena nobingnd likrisk liklead
## 1 0 0 1 0 0 0 1 2 4
## 2 0 1 0 0 0 0 2 0 0
## 3 0 1 0 0 0 0 2 0 3
## 4 1 0 0 0 0 0 2 0 1
## 5 0 1 0 0 0 0 2 1 0
## 6 0 1 0 0 0 0 2 2 4
## sothnds actcomp mascfel femifel impbemw trmedmw trwrkmw trplcmw trmdcnt
## 1 4 5 4 0 3 3 3 3 3
## 2 6 6 3 6 3 3 2 3 1
## 3 6 6 0 6 5 3 3 3 1
## 4 6 6 0 6 5 3 1 3 3
## 5 6 6 0 5 5 3 3 3 3
## 6 5 3 6 6 6 3 2 3 3
## trwkcnt trplcnt eqwrkbg eqpolbg eqmgmbg eqpaybg eqparep eqparlv freinsw
## 1 3 3 6 6 6 6 4 4 4
## 2 1 8 6 5 5 5 2 4 1
## 3 1 1 5 6 6 6 2 8 2
## 4 1 2 5 5 5 6 1 8 4
## 5 1 3 6 6 6 6 1 5 1
## 6 1 3 5 5 5 6 2 3 2
## fineqpy wsekpwr weasoff wlespdm wexashr wprtbym wbrgwrm hhmmb gndr gndr2
## 1 3 2 3 2 2 2 2 2 1 2
## 2 2 3 3 4 2 2 3 1 2 6
## 3 1 2 2 4 2 4 2 3 2 1
## 4 1 3 3 4 2 3 2 1 2 6
## 5 1 2 2 4 1 3 3 2 1 1
## 6 1 3 4 4 4 3 1 2 2 1
## gndr3 gndr4 gndr5 gndr6 gndr7 gndr8 gndr9 gndr10 gndr11 gndr12 gndr13 yrbrn
## 1 6 6 6 6 6 NA NA NA NA NA NA 1958
## 2 6 6 6 6 6 NA NA NA NA NA NA 2002
## 3 2 6 6 6 6 NA NA NA NA NA NA 1970
## 4 6 6 6 6 6 NA NA NA NA NA NA 1945
## 5 6 6 6 6 6 NA NA NA NA NA NA 1959
## 6 6 6 6 6 6 NA NA NA NA NA NA 1964
## agea agegroup yrbrn2 yrbrn3 yrbrn4 yrbrn5 yrbrn6 yrbrn7 yrbrn8 yrbrn9 yrbrn10
## 1 65 6 1957 6666 6666 6666 6666 6666 NA NA NA
## 2 21 1 6666 6666 6666 6666 6666 6666 NA NA NA
## 3 53 4 1970 2001 6666 6666 6666 6666 NA NA NA
## 4 78 7 6666 6666 6666 6666 6666 6666 NA NA NA
## 5 64 5 1962 6666 6666 6666 6666 6666 NA NA NA
## 6 59 5 1956 6666 6666 6666 6666 6666 NA NA NA
## yrbrn11 yrbrn12 yrbrn13 rshipa2 rshipa3 rshipa4 rshipa5 rshipa6 rshipa7
## 1 NA NA NA 1 66 66 66 66 66
## 2 NA NA NA 66 66 66 66 66 66
## 3 NA NA NA 1 2 66 66 66 66
## 4 NA NA NA 66 66 66 66 66 66
## 5 NA NA NA 1 66 66 66 66 66
## 6 NA NA NA 1 66 66 66 66 66
## rshipa8 rshipa9 rshipa10 rshipa11 rshipa12 rshipa13 rshipa15 rshpsts rshpsgb
## 1 NA NA NA NA NA NA NA 1 NA
## 2 NA NA NA NA NA NA NA 66 NA
## 3 NA NA NA NA NA NA NA 1 NA
## 4 NA NA NA NA NA NA NA 66 NA
## 5 NA NA NA NA NA NA NA 1 NA
## 6 NA NA NA NA NA NA NA 1 NA
## lvgptnea dvrcdeva marsts marstgb maritalb chldhhe domicil paccmoro paccdwlr
## 1 1 2 66 NA 1 1 3 0 0
## 2 2 2 6 NA 6 2 1 1 0
## 3 1 2 66 NA 1 6 3 0 0
## 4 1 1 4 NA 4 1 1 0 0
## 5 1 2 66 NA 1 1 4 0 0
## 6 1 1 66 NA 1 1 4 0 0
## pacclift paccnbsh paccocrw paccxhoc paccnois paccinro paccnt paccref paccdk
## 1 0 0 0 0 0 0 1 0 0
## 2 0 0 0 0 0 0 0 0 0
## 3 0 0 0 0 0 0 1 0 0
## 4 0 0 0 0 0 0 1 0 0
## 5 0 0 0 0 0 0 1 0 0
## 6 0 0 0 0 0 0 1 0 0
## paccna edulvlb eisced edlveat edlvebe edlvebg edlvehr edlvgcy edlvdee edlvdfi
## 1 0 322 3 6 NA NA NA NA NA NA
## 2 0 423 5 10 NA NA NA NA NA NA
## 3 0 610 6 12 NA NA NA NA NA NA
## 4 0 422 5 9 NA NA NA NA NA NA
## 5 0 322 3 6 NA NA NA NA NA NA
## 6 0 313 4 8 NA NA NA NA NA NA
## edlvdfr edudde1 educde2 edlvegr edlvdahu edlvdis edlvdie edubil1 eduail2
## 1 NA NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA NA
## edlvfit edlvelv edlvdlt edlveme edlvenl edlveno edlvipl edlvept edlvdrs
## 1 NA NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA NA
## edlvdsk edlvesi edlvies edlvdse edlvdch edlvdua educgb1 edubgb2 edagegb
## 1 NA NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA NA
## eduyrs pdwrk edctn uempla uempli dsbld rtrd cmsrv hswrk dngoth dngref dngdk
## 1 12 0 0 0 0 0 1 0 0 0 0 0
## 2 14 0 1 0 0 0 0 0 0 0 0 0
## 3 16 1 0 0 0 0 0 0 0 0 0 0
## 4 14 0 0 0 0 0 1 0 0 0 0 0
## 5 12 0 0 0 0 0 1 0 0 0 0 0
## 6 16 1 0 0 0 0 0 0 0 0 0 0
## dngna mainact mnactic crpdwk pdjobev pdjobyr emplrel emplno wrkctra estsz
## 1 0 66 6 2 2 6666 6 66666 6 6
## 2 0 66 2 2 1 2023 1 66666 2 2
## 3 0 66 1 6 6 6666 1 66666 1 1
## 4 0 66 6 2 1 2005 1 66666 1 5
## 5 0 66 6 2 1 2021 1 66666 1 2
## 6 0 66 1 6 6 6666 1 66666 1 5
## jbspv njbspv wkdcorga iorgact wkhct wkhtot nacer2 tporgwk isco08 wrkac6m
## 1 6 66666 66 66 666 666 666 66 66666 6
## 2 2 66666 0 0 32 32 14 4 5249 2
## 3 1 4 10 9 25 25 88 6 2635 2
## 4 2 66666 5 0 39 39 87 2 2221 2
## 5 2 66666 7 7 40 35 47 4 5223 2
## 6 1 12 10 7 40 40 21 4 1112 2
## uemp3m uemp12m uemp5yr mbtru hincsrca hinctnta hincfel edulvlpb eiscedp
## 1 2 6 6 3 4 6 1 322 3
## 2 2 6 6 3 8 1 2 6666 66
## 3 2 6 6 3 1 5 1 520 5
## 4 2 6 6 3 4 2 2 6666 66
## 5 2 6 6 2 4 77 2 322 3
## 6 2 6 6 1 1 9 1 322 3
## edlvpfat edlvpebe edlvpebg edlvpehr edlvpgcy edlvpdee edlvpdfi edlvpdfr
## 1 6 NA NA NA NA NA NA NA
## 2 6666 NA NA NA NA NA NA NA
## 3 11 NA NA NA NA NA NA NA
## 4 6666 NA NA NA NA NA NA NA
## 5 6 NA NA NA NA NA NA NA
## 6 6 NA NA NA NA NA NA NA
## edupdde1 edupcde2 edlvpegr edlvpdahu edlvpdis edlvpdie edupail2 edupbil1
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## edlvpfit edlvpelv edlvpdlt edlvpeme edlvpenl edlvpeno edlvphpl edlvpept
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## edlvpdrs edlvpdsk edlvpesi edlvphes edlvpdse edlvpdch edlvpdua edupcgb1
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## edupbgb2 edagepgb pdwrkp edctnp uemplap uemplip dsbldp rtrdp cmsrvp hswrkp
## 1 NA NA 0 0 0 0 0 1 0 0
## 2 NA NA 0 0 0 0 0 0 0 0
## 3 NA NA 1 0 0 0 0 0 0 0
## 4 NA NA 0 0 0 0 0 0 0 0
## 5 NA NA 0 0 0 0 0 1 0 0
## 6 NA NA 1 0 0 0 0 0 0 0
## dngothp dngdkp dngnapp dngrefp dngnap mnactp crpdwkp isco08p emprelp wkhtotp
## 1 0 0 0 0 0 66 2 66666 6 666
## 2 0 0 1 0 0 66 6 66666 6 666
## 3 0 0 0 0 0 66 6 2635 1 1
## 4 0 0 1 0 0 66 6 66666 6 666
## 5 0 0 0 0 0 66 2 66666 6 666
## 6 0 0 0 0 0 66 6 3321 2 1
## edulvlfb eiscedf edlvfeat edlvfebe edlvfebg edlvfehr edlvfgcy edlvfdee
## 1 322 3 7 NA NA NA NA NA
## 2 322 3 6 NA NA NA NA NA
## 3 322 3 6 NA NA NA NA NA
## 4 322 3 6 NA NA NA NA NA
## 5 322 3 6 NA NA NA NA NA
## 6 800 7 18 NA NA NA NA NA
## edlvfdfi edlvfdfr edufcde1 edufbde2 edlvfegr edlvfdahu edlvfdis edlvfdie
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## edufbil1 edufail2 edlvffit edlvfelv edlvfdlt edlvfeme edlvfenl edlvfeno
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## edlvfgpl edlvfept edlvfdrs edlvfdsk edlvfesi edlvfges edlvfdse edlvfdch
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## edlvfdua edufcgb1 edufbgb2 edagefgb emprf14 occf14b edulvlmb eiscedm edlvmeat
## 1 NA NA NA NA 2 9 212 2 3
## 2 NA NA NA NA 2 9 322 3 6
## 3 NA NA NA NA 1 6 322 3 7
## 4 NA NA NA NA 1 5 212 2 3
## 5 NA NA NA NA 1 4 212 2 3
## 6 NA NA NA NA 1 1 610 6 13
## edlvmebe edlvmebg edlvmehr edlvmgcy edlvmdee edlvmdfi edlvmdfr edumcde1
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## edumbde2 edlvmegr edlvmdahu edlvmdis edlvmdie edumbil1 edumail2 edlvmfit
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## edlvmelv edlvmdlt edlvmeme edlvmenl edlvmeno edlvmgpl edlvmept edlvmdrs
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## edlvmdsk edlvmesi edlvmges edlvmdse edlvmdch edlvmdua edumcgb1 edumbgb2
## 1 NA NA NA NA NA NA NA NA
## 2 NA NA NA NA NA NA NA NA
## 3 NA NA NA NA NA NA NA NA
## 4 NA NA NA NA NA NA NA NA
## 5 NA NA NA NA NA NA NA NA
## 6 NA NA NA NA NA NA NA NA
## edagemgb emprm14 occm14b atncrse anctrya1 anctrya2 regunit region ipcrtiva
## 1 NA 2 9 2 11010 555555 2 AT31 3
## 2 NA 2 9 2 11010 555555 2 AT22 2
## 3 NA 3 66 1 11010 11070 2 AT33 1
## 4 NA 1 4 2 14090 11010 2 AT31 3
## 5 NA 1 7 2 11010 11018 2 AT32 3
## 6 NA 1 1 2 11010 11018 2 AT33 1
## impricha ipeqopta ipshabta impsafea impdiffa ipfrulea ipudrsta ipmodsta
## 1 5 2 2 2 4 2 2 2
## 2 4 2 4 4 4 4 2 2
## 3 4 1 3 2 4 3 1 3
## 4 4 2 3 1 4 3 3 2
## 5 4 2 2 2 4 5 2 3
## 6 2 2 1 2 2 2 2 3
## ipgdtima impfreea iphlppla ipsucesa ipstrgva ipadvnta ipbhprpa iprspota
## 1 2 2 2 3 2 5 2 2
## 2 2 2 1 4 2 4 2 4
## 3 3 2 1 3 2 4 3 3
## 4 3 2 2 3 3 4 3 3
## 5 3 2 2 2 2 4 2 2
## 6 2 2 1 2 1 3 1 2
## iplylfra impenva imptrada impfuna testji1 testji2 testji3 testji4 testji5
## 1 2 2 3 3 6 6 6 3 3
## 2 1 1 4 2 6 6 6 6 6
## 3 1 1 3 2 6 6 6 8 8
## 4 2 2 2 3 6 6 6 1 1
## 5 2 2 2 2 6 6 6 6 6
## 6 1 2 2 2 6 6 6 6 6
## testji6 testji7 testji8 testji9 respc19a symtc19 symtnc19 vacc19 recon
## 1 2 66 66 66 1 2 6 1 2
## 2 6 10 2 2 1 2 6 1 1
## 3 8 66 66 66 1 2 6 1 1
## 4 1 66 66 66 1 2 6 1 2
## 5 6 8 4 3 3 6 6 1 2
## 6 6 7 4 1 1 2 6 1 2
## inwds ainws ainwe
## 1 2023-11-12 14:49:50 2023-11-12 14:49:50 2023-11-12 14:50:23
## 2 2023-10-18 09:56:32 2023-10-18 09:56:32 2023-10-18 09:58:32
## 3 2023-09-30 13:22:49 2023-09-30 13:22:49 2023-09-30 13:24:24
## 4 2023-06-30 14:31:46 2023-06-30 14:31:46 2023-06-30 14:32:40
## 5 2023-07-11 10:11:00 2023-07-11 10:11:00 2023-07-11 10:13:36
## 6 2023-10-16 08:35:24 2023-10-16 08:35:24 2023-10-16 08:37:00
## binwe cinwe dinwe
## 1 2023-11-12 15:01:14 2023-11-12 15:03:07 2023-11-12 15:08:28
## 2 2023-10-18 10:07:21 2023-10-18 10:11:42 2023-10-18 10:19:27
## 3 2023-09-30 13:34:23 2023-09-30 13:41:50 2023-09-30 13:50:25
## 4 2023-06-30 14:42:30 2023-06-30 14:50:31 2023-06-30 14:53:56
## 5 2023-07-11 10:18:33 2023-07-11 10:23:56 2023-07-11 10:43:23
## 6 2023-10-16 08:49:01 2023-10-16 08:55:53 2023-10-16 09:07:39
## einwe finwe hinwe
## 1 2023-11-12 15:14:58 2023-11-12 15:18:41 2023-11-12 15:20:19
## 2 2023-10-18 10:25:47 2023-10-18 10:32:34 2023-10-18 10:36:39
## 3 2023-09-30 13:56:10 2023-09-30 14:03:15 2023-09-30 14:05:12
## 4 2023-06-30 14:57:00 2023-06-30 15:04:03 2023-06-30 15:05:22
## 5 2023-07-11 10:56:16 2023-07-11 11:03:31 2023-07-11 11:07:49
## 6 2023-10-16 09:14:29 2023-10-16 09:29:26 2023-10-16 09:32:29
## iinwe kinwe rinwe inwde
## 1 2023-11-12 15:20:37 2023-11-12 15:20:46 2023-11-12 15:26:55
## 2 2023-10-18 10:37:18 2023-10-18 10:37:49 2023-10-18 10:44:18
## 3 2023-09-30 14:05:27 2023-09-30 14:05:41 2023-09-30 14:13:33
## 4 2023-06-30 15:05:41 2023-06-30 15:06:02 2023-06-30 15:11:21
## 5 2023-07-11 11:08:12 2023-07-11 11:08:26 2023-07-11 11:14:03
## 6 2023-10-16 09:33:12 2023-10-16 09:33:34 2023-10-16 09:42:52
## jinws jinwe inwtm mode domain prob
## 1 2023-11-12 15:21:28 2023-11-12 15:26:55 30 1 2 0.0005786479
## 2 2023-10-18 10:42:22 2023-10-18 10:44:18 40 1 1 0.0011243912
## 3 2023-09-30 14:08:31 2023-09-30 14:13:33 42 1 2 0.0004925300
## 4 2023-06-30 15:08:05 2023-06-30 15:11:21 34 1 1 0.0012332522
## 5 2023-07-11 11:10:02 2023-07-11 11:14:03 57 1 2 0.0009487666
## 6 2023-10-16 09:38:14 2023-10-16 09:42:52 57 1 2 0.0006908728
## stratum psu
## 1 107 317
## 2 69 128
## 3 18 418
## 4 101 295
## 5 115 344
## 6 7 3733. Variable Selection
The following variables are selected based on theoretical relevance and data availability:
hincfel: Feeling about household income (target variable)cntry: Country of residencegndr: Genderagegroup: Age groupeisced: Education leveluemp12m: Unemployment experience in the last 12 monthshealth: Self-rated healthhappy: Self-reported happiness
These variables capture economic, demographic, and subjective well-being dimensions.
colnames(ess)## [1] "name" "essround" "edition" "proddate" "idno" "cntry"
## [7] "dweight" "pspwght" "pweight" "anweight" "nwspol" "netusoft"
## [13] "netustm" "ppltrst" "pplfair" "pplhlp" "polintr" "psppsgva"
## [19] "actrolga" "psppipla" "cptppola" "trstprl" "trstlgl" "trstplc"
## [25] "trstplt" "trstprt" "trstep" "trstun" "vote" "prtvtdat"
## [31] "prtvtebe" "prtvtfbg" "prtvtchr" "prtvtccy" "prtvtiee" "prtvtffi"
## [37] "prtvtffr" "prtvgde1" "prtvgde2" "prtvtegr" "prtvthhu" "prtvteis"
## [43] "prtvteie" "prtvteil" "prtvteit" "prtvtblv" "prtvclt1" "prtvclt2"
## [49] "prtvclt3" "prtvtbme" "prtvtinl" "prtvtcno" "prtvtfpl" "prtvtept"
## [55] "prtvtbrs" "prtvtesk" "prtvtgsi" "prtvtges" "prtvtese" "prtvthch"
## [61] "prtvtdua" "prtvtdgb" "contplt" "donprty" "badge" "sgnptit"
## [67] "pbldmna" "bctprd" "pstplonl" "volunfp" "clsprty" "prtcleat"
## [73] "prtclebe" "prtclfbg" "prtclbhr" "prtclccy" "prtcliee" "prtclgfi"
## [79] "prtclgfr" "prtclgde" "prtclegr" "prtclihu" "prtcleis" "prtclfie"
## [85] "prtclfil" "prtclfit" "prtclblv" "prtclclt" "prtclbme" "prtclhnl"
## [91] "prtclcno" "prtcljpl" "prtclgpt" "prtclbrs" "prtclesk" "prtclgsi"
## [97] "prtclhes" "prtclese" "prtclhch" "prtcleua" "prtcldgb" "prtdgcl"
## [103] "lrscale" "stflife" "stfeco" "stfgov" "stfdem" "stfedu"
## [109] "stfhlth" "gincdif" "freehms" "hmsfmlsh" "hmsacld" "euftf"
## [115] "lrnobed" "loylead" "imsmetn" "imdfetn" "impcntr" "imbgeco"
## [121] "imueclt" "imwbcnt" "happy" "sclmeet" "inprdsc" "sclact"
## [127] "crmvct" "aesfdrk" "health" "hlthhmp" "atchctr" "atcherp"
## [133] "rlgblg" "rlgdnm" "rlgdnbat" "rlgdncy" "rlgdnafi" "rlgdnade"
## [139] "rlgdnagr" "rlgdnhu" "rlgdnais" "rlgdnie" "rlgdnlv" "rlgdnlt"
## [145] "rlgdme" "rlgdnanl" "rlgdnno" "rlgdnapl" "rlgdnapt" "rlgdnrs"
## [151] "rlgdnask" "rlgdnase" "rlgdnach" "rlgdnaua" "rlgdngb" "rlgblge"
## [157] "rlgdnme" "rlgdebat" "rlgdecy" "rlgdeafi" "rlgdeade" "rlgdeagr"
## [163] "rlgdehu" "rlgdeais" "rlgdeie" "rlgdelv" "rlgdelt" "rlgdeme"
## [169] "rlgdeanl" "rlgdeno" "rlgdeapl" "rlgdeapt" "rlgders" "rlgdeask"
## [175] "rlgdease" "rlgdeach" "rlgdeaua" "rlgdegb" "rlgdgr" "rlgatnd"
## [181] "pray" "dscrgrp" "dscrrce" "dscrntn" "dscrrlg" "dscrlng"
## [187] "dscretn" "dscrage" "dscrgnd" "dscrsex" "dscrdsb" "dscroth"
## [193] "dscrdk" "dscrref" "dscrnap" "dscrna" "ctzcntr" "brncntr"
## [199] "cntbrthd" "livecnta" "lnghom1" "lnghom2" "feethngr" "facntr"
## [205] "fbrncntc" "mocntr" "mbrncntc" "ccnthum" "ccrdprs" "wrclmch"
## [211] "admrclc" "testjc34" "testjc35" "testjc36" "testjc37" "testjc38"
## [217] "testjc39" "testjc40" "testjc41" "testjc42" "vteurmmb" "vteubcmb"
## [223] "ctrlife" "etfruit" "eatveg" "dosprt" "cgtsmok" "alcfreq"
## [229] "alcwkdy" "alcwknd" "icgndra" "alcbnge" "height" "weighta"
## [235] "dshltgp" "dshltms" "dshltnt" "dshltref" "dshltdk" "dshltna"
## [241] "medtrun" "medtrnp" "medtrnt" "medtroc" "medtrnl" "medtrwl"
## [247] "medtrnaa" "medtroth" "medtrnap" "medtrref" "medtrdk" "medtrna"
## [253] "medtrnu" "hlpfmly" "hlpfmhr" "trhltacu" "trhltacp" "trhltcm"
## [259] "trhltch" "trhltos" "trhltho" "trhltht" "trhlthy" "trhltmt"
## [265] "trhltpt" "trhltre" "trhltsh" "trhltnt" "trhltref" "trhltdk"
## [271] "trhltna" "fltdpr" "flteeff" "slprl" "wrhpp" "fltlnl"
## [277] "enjlf" "fltsd" "cldgng" "hltprhc" "hltprhb" "hltprbp"
## [283] "hltpral" "hltprbn" "hltprpa" "hltprpf" "hltprsd" "hltprsc"
## [289] "hltprsh" "hltprdi" "hltprnt" "hltprref" "hltprdk" "hltprna"
## [295] "hltphhc" "hltphhb" "hltphbp" "hltphal" "hltphbn" "hltphpa"
## [301] "hltphpf" "hltphsd" "hltphsc" "hltphsh" "hltphdi" "hltphnt"
## [307] "hltphnap" "hltphref" "hltphdk" "hltphna" "hltprca" "cancfre"
## [313] "cnfpplh" "fnsdfml" "jbexpvi" "jbexpti" "jbexpml" "jbexpmc"
## [319] "jbexpnt" "jbexpnap" "jbexpref" "jbexpdk" "jbexpna" "jbexevl"
## [325] "jbexevh" "jbexevc" "jbexera" "jbexecp" "jbexebs" "jbexent"
## [331] "jbexenap" "jbexeref" "jbexedk" "jbexena" "nobingnd" "likrisk"
## [337] "liklead" "sothnds" "actcomp" "mascfel" "femifel" "impbemw"
## [343] "trmedmw" "trwrkmw" "trplcmw" "trmdcnt" "trwkcnt" "trplcnt"
## [349] "eqwrkbg" "eqpolbg" "eqmgmbg" "eqpaybg" "eqparep" "eqparlv"
## [355] "freinsw" "fineqpy" "wsekpwr" "weasoff" "wlespdm" "wexashr"
## [361] "wprtbym" "wbrgwrm" "hhmmb" "gndr" "gndr2" "gndr3"
## [367] "gndr4" "gndr5" "gndr6" "gndr7" "gndr8" "gndr9"
## [373] "gndr10" "gndr11" "gndr12" "gndr13" "yrbrn" "agea"
## [379] "agegroup" "yrbrn2" "yrbrn3" "yrbrn4" "yrbrn5" "yrbrn6"
## [385] "yrbrn7" "yrbrn8" "yrbrn9" "yrbrn10" "yrbrn11" "yrbrn12"
## [391] "yrbrn13" "rshipa2" "rshipa3" "rshipa4" "rshipa5" "rshipa6"
## [397] "rshipa7" "rshipa8" "rshipa9" "rshipa10" "rshipa11" "rshipa12"
## [403] "rshipa13" "rshipa15" "rshpsts" "rshpsgb" "lvgptnea" "dvrcdeva"
## [409] "marsts" "marstgb" "maritalb" "chldhhe" "domicil" "paccmoro"
## [415] "paccdwlr" "pacclift" "paccnbsh" "paccocrw" "paccxhoc" "paccnois"
## [421] "paccinro" "paccnt" "paccref" "paccdk" "paccna" "edulvlb"
## [427] "eisced" "edlveat" "edlvebe" "edlvebg" "edlvehr" "edlvgcy"
## [433] "edlvdee" "edlvdfi" "edlvdfr" "edudde1" "educde2" "edlvegr"
## [439] "edlvdahu" "edlvdis" "edlvdie" "edubil1" "eduail2" "edlvfit"
## [445] "edlvelv" "edlvdlt" "edlveme" "edlvenl" "edlveno" "edlvipl"
## [451] "edlvept" "edlvdrs" "edlvdsk" "edlvesi" "edlvies" "edlvdse"
## [457] "edlvdch" "edlvdua" "educgb1" "edubgb2" "edagegb" "eduyrs"
## [463] "pdwrk" "edctn" "uempla" "uempli" "dsbld" "rtrd"
## [469] "cmsrv" "hswrk" "dngoth" "dngref" "dngdk" "dngna"
## [475] "mainact" "mnactic" "crpdwk" "pdjobev" "pdjobyr" "emplrel"
## [481] "emplno" "wrkctra" "estsz" "jbspv" "njbspv" "wkdcorga"
## [487] "iorgact" "wkhct" "wkhtot" "nacer2" "tporgwk" "isco08"
## [493] "wrkac6m" "uemp3m" "uemp12m" "uemp5yr" "mbtru" "hincsrca"
## [499] "hinctnta" "hincfel" "edulvlpb" "eiscedp" "edlvpfat" "edlvpebe"
## [505] "edlvpebg" "edlvpehr" "edlvpgcy" "edlvpdee" "edlvpdfi" "edlvpdfr"
## [511] "edupdde1" "edupcde2" "edlvpegr" "edlvpdahu" "edlvpdis" "edlvpdie"
## [517] "edupail2" "edupbil1" "edlvpfit" "edlvpelv" "edlvpdlt" "edlvpeme"
## [523] "edlvpenl" "edlvpeno" "edlvphpl" "edlvpept" "edlvpdrs" "edlvpdsk"
## [529] "edlvpesi" "edlvphes" "edlvpdse" "edlvpdch" "edlvpdua" "edupcgb1"
## [535] "edupbgb2" "edagepgb" "pdwrkp" "edctnp" "uemplap" "uemplip"
## [541] "dsbldp" "rtrdp" "cmsrvp" "hswrkp" "dngothp" "dngdkp"
## [547] "dngnapp" "dngrefp" "dngnap" "mnactp" "crpdwkp" "isco08p"
## [553] "emprelp" "wkhtotp" "edulvlfb" "eiscedf" "edlvfeat" "edlvfebe"
## [559] "edlvfebg" "edlvfehr" "edlvfgcy" "edlvfdee" "edlvfdfi" "edlvfdfr"
## [565] "edufcde1" "edufbde2" "edlvfegr" "edlvfdahu" "edlvfdis" "edlvfdie"
## [571] "edufbil1" "edufail2" "edlvffit" "edlvfelv" "edlvfdlt" "edlvfeme"
## [577] "edlvfenl" "edlvfeno" "edlvfgpl" "edlvfept" "edlvfdrs" "edlvfdsk"
## [583] "edlvfesi" "edlvfges" "edlvfdse" "edlvfdch" "edlvfdua" "edufcgb1"
## [589] "edufbgb2" "edagefgb" "emprf14" "occf14b" "edulvlmb" "eiscedm"
## [595] "edlvmeat" "edlvmebe" "edlvmebg" "edlvmehr" "edlvmgcy" "edlvmdee"
## [601] "edlvmdfi" "edlvmdfr" "edumcde1" "edumbde2" "edlvmegr" "edlvmdahu"
## [607] "edlvmdis" "edlvmdie" "edumbil1" "edumail2" "edlvmfit" "edlvmelv"
## [613] "edlvmdlt" "edlvmeme" "edlvmenl" "edlvmeno" "edlvmgpl" "edlvmept"
## [619] "edlvmdrs" "edlvmdsk" "edlvmesi" "edlvmges" "edlvmdse" "edlvmdch"
## [625] "edlvmdua" "edumcgb1" "edumbgb2" "edagemgb" "emprm14" "occm14b"
## [631] "atncrse" "anctrya1" "anctrya2" "regunit" "region" "ipcrtiva"
## [637] "impricha" "ipeqopta" "ipshabta" "impsafea" "impdiffa" "ipfrulea"
## [643] "ipudrsta" "ipmodsta" "ipgdtima" "impfreea" "iphlppla" "ipsucesa"
## [649] "ipstrgva" "ipadvnta" "ipbhprpa" "iprspota" "iplylfra" "impenva"
## [655] "imptrada" "impfuna" "testji1" "testji2" "testji3" "testji4"
## [661] "testji5" "testji6" "testji7" "testji8" "testji9" "respc19a"
## [667] "symtc19" "symtnc19" "vacc19" "recon" "inwds" "ainws"
## [673] "ainwe" "binwe" "cinwe" "dinwe" "einwe" "finwe"
## [679] "hinwe" "iinwe" "kinwe" "rinwe" "inwde" "jinws"
## [685] "jinwe" "inwtm" "mode" "domain" "prob" "stratum"
## [691] "psu"##Select variables (broad & meaningful)
ess_sub <- ess %>%
select(
hincfel, # Feeling about household income (TARGET)
cntry, # Country (broad geographical coverage)
gndr, # Gender
agegroup, # Age group
eisced, # Education level
uemp12m, # Unemployed last 12 months
health, # Subjective health
happy # Happiness
)4. Data Cleaning and Recoding
ESS-specific missing and non-substantive responses (e.g.,
Refusal, Don’t know) are removed.
Numeric variables are recoded into meaningful categorical
groups to ensure compatibility with association rule
mining.
The target variable hincfel is recoded into four
categories: - Living comfortably - Coping - Difficult - Very
difficult
ess_clean <- ess_sub %>%
filter(
hincfel %in% 1:4,
gndr %in% 1:2,
!is.na(agegroup),
eisced > 0 & eisced < 9,
uemp12m %in% 1:2,
health %in% 1:5,
happy %in% 0:10
) %>%
mutate(
# TARGET
hincfel = factor(
hincfel,
levels = 1:4,
labels = c("Living comfortably", "Coping", "Difficult", "Very difficult")
),
gndr = factor(gndr, labels = c("Male", "Female")),
agegroup = factor(agegroup),
eisced = case_when(
eisced <= 2 ~ "Low education",
eisced <= 5 ~ "Medium education",
TRUE ~ "High education"
),
uemp12m = factor(
uemp12m,
labels = c("Unemployed", "Not unemployed")
),
health = case_when(
health <= 2 ~ "Good health",
health == 3 ~ "Fair health",
TRUE ~ "Bad health"
),
happy = case_when(
happy <= 4 ~ "Low happiness",
happy <= 7 ~ "Medium happiness",
TRUE ~ "High happiness"
),
cntry = factor(cntry)
)5. Transaction Construction
Each survey respondent is treated as a single
transaction, and each categorical response is treated as an
item.
The cleaned dataset is converted into a transactions
object, which is required for association rule analysis.
ess_trans <- as(ess_clean, "transactions")
summary(ess_trans)## transactions as itemMatrix in sparse format with
## 13004 rows (elements/itemsets/transactions) and
## 55 columns (items) and a density of 0.1454545
##
## most frequent items:
## health=Good health uemp12m=Not unemployed eisced=Medium education
## 7880 7576 7119
## gndr=Female happy=High happiness (Other)
## 7022 6407 68028
##
## element (itemset/transaction) length distribution:
## sizes
## 8
## 13004
##
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8 8 8 8 8 8
##
## includes extended item information - examples:
## labels variables levels
## 1 hincfel=Living comfortably hincfel Living comfortably
## 2 hincfel=Coping hincfel Coping
## 3 hincfel=Difficult hincfel Difficult
##
## includes extended transaction information - examples:
## transactionID
## 1 1
## 2 2
## 3 36. Association Rule Mining
Association rules are generated using the Apriori
algorithm.
The analysis is constrained such that:
hincfelappears only on the right-hand side (consequent) of the rules- Minimum support and confidence thresholds are applied to ensure statistical relevance
Rules are evaluated using: - Support - Confidence - Lift
rules <- apriori(
ess_trans,
parameter = list(
supp = 0.02,
conf = 0.4,
minlen = 2
),
appearance = list(
rhs = paste0("hincfel=", levels(ess_clean$hincfel)),
default = "lhs"
)
)## Apriori
##
## Parameter specification:
## confidence minval smax arem aval originalSupport maxtime support minlen
## 0.4 0.1 1 none FALSE TRUE 5 0.02 2
## maxlen target ext
## 10 rules TRUE
##
## Algorithmic control:
## filter tree heap memopt load sort verbose
## 0.1 TRUE TRUE FALSE TRUE 2 TRUE
##
## Absolute minimum support count: 260
##
## set item appearances ...[4 item(s)] done [0.00s].
## set transactions ...[55 item(s), 13004 transaction(s)] done [0.00s].
## sorting and recoding items ... [51 item(s)] done [0.00s].
## creating transaction tree ... done [0.00s].
## checking subsets of size 1 2 3 4 5 6 done [0.01s].
## writing ... [323 rule(s)] done [0.00s].
## creating S4 object ... done [0.00s].##Sort & inspect rules
rules_sorted <- sort(rules, by = "lift", decreasing = TRUE)
inspect(head(rules_sorted, 10))## lhs rhs support confidence coverage lift count
## [1] {gndr=Male,
## eisced=High education,
## health=Good health,
## happy=High happiness} => {hincfel=Living comfortably} 0.02891418 0.5570370 0.05190711 2.411355 376
## [2] {gndr=Male,
## eisced=High education,
## uemp12m=Not unemployed,
## health=Good health,
## happy=High happiness} => {hincfel=Living comfortably} 0.02091664 0.5506073 0.03798831 2.383521 272
## [3] {gndr=Male,
## eisced=High education,
## happy=High happiness} => {hincfel=Living comfortably} 0.03329745 0.5325953 0.06251922 2.305549 433
## [4] {gndr=Male,
## eisced=High education,
## uemp12m=Not unemployed,
## happy=High happiness} => {hincfel=Living comfortably} 0.02430022 0.5302013 0.04583205 2.295186 316
## [5] {eisced=High education,
## uemp12m=Not unemployed,
## health=Good health,
## happy=High happiness} => {hincfel=Living comfortably} 0.04344817 0.5226642 0.08312827 2.262558 565
## [6] {eisced=High education,
## health=Good health,
## happy=High happiness} => {hincfel=Living comfortably} 0.05959705 0.5019430 0.11873270 2.172858 775
## [7] {gndr=Female,
## eisced=High education,
## uemp12m=Not unemployed,
## health=Good health,
## happy=High happiness} => {hincfel=Living comfortably} 0.02253153 0.4991482 0.04513996 2.160760 293
## [8] {eisced=High education,
## uemp12m=Not unemployed,
## happy=High happiness} => {hincfel=Living comfortably} 0.05021532 0.4950720 0.10143033 2.143115 653
## [9] {gndr=Male,
## eisced=High education,
## uemp12m=Not unemployed,
## health=Good health} => {hincfel=Living comfortably} 0.02899108 0.4870801 0.05952015 2.108519 377
## [10] {eisced=High education,
## happy=High happiness} => {hincfel=Living comfortably} 0.06959397 0.4728318 0.14718548 2.046839 9057. Rule Selection and Evaluation
The generated rules are sorted by lift, highlighting
the strongest associations.
Only rules with: - Confidence above 0.5
- Lift greater than 1
are retained for interpretation, ensuring that the identified patterns are both reliable and meaningful.
strong_rules <- subset(
rules_sorted,
lift > 1.2 & confidence > 0.5
)
inspect(strong_rules)## lhs rhs support confidence coverage lift count
## [1] {gndr=Male,
## eisced=High education,
## health=Good health,
## happy=High happiness} => {hincfel=Living comfortably} 0.02891418 0.5570370 0.05190711 2.411355 376
## [2] {gndr=Male,
## eisced=High education,
## uemp12m=Not unemployed,
## health=Good health,
## happy=High happiness} => {hincfel=Living comfortably} 0.02091664 0.5506073 0.03798831 2.383521 272
## [3] {gndr=Male,
## eisced=High education,
## happy=High happiness} => {hincfel=Living comfortably} 0.03329745 0.5325953 0.06251922 2.305549 433
## [4] {gndr=Male,
## eisced=High education,
## uemp12m=Not unemployed,
## happy=High happiness} => {hincfel=Living comfortably} 0.02430022 0.5302013 0.04583205 2.295186 316
## [5] {eisced=High education,
## uemp12m=Not unemployed,
## health=Good health,
## happy=High happiness} => {hincfel=Living comfortably} 0.04344817 0.5226642 0.08312827 2.262558 565
## [6] {eisced=High education,
## health=Good health,
## happy=High happiness} => {hincfel=Living comfortably} 0.05959705 0.5019430 0.11873270 2.172858 775
## [7] {cntry=EE} => {hincfel=Coping} 0.02153184 0.6126915 0.03514303 1.384197 280
## [8] {cntry=FI} => {hincfel=Coping} 0.02529991 0.6058932 0.04175638 1.368839 329
## [9] {eisced=Medium education,
## health=Fair health,
## happy=High happiness} => {hincfel=Coping} 0.03944940 0.5588235 0.07059366 1.262498 513
## [10] {cntry=RS} => {hincfel=Coping} 0.02868348 0.5517751 0.05198400 1.246575 373
## [11] {gndr=Female,
## eisced=Medium education,
## health=Fair health,
## happy=High happiness} => {hincfel=Coping} 0.02422332 0.5487805 0.04414026 1.239809 315
## [12] {eisced=Medium education,
## uemp12m=Not unemployed,
## health=Fair health,
## happy=High happiness} => {hincfel=Coping} 0.02153184 0.5458090 0.03944940 1.233096 280
## [13] {agegroup=4,
## eisced=Medium education,
## uemp12m=Not unemployed,
## health=Good health} => {hincfel=Coping} 0.02322362 0.5421903 0.04283297 1.224921 302
## [14] {gndr=Male,
## health=Fair health,
## happy=High happiness} => {hincfel=Coping} 0.02491541 0.5409015 0.04606275 1.222009 324
## [15] {gndr=Male,
## eisced=Medium education,
## uemp12m=Not unemployed,
## health=Good health,
## happy=Medium happiness} => {hincfel=Coping} 0.02345432 0.5360281 0.04375577 1.210999 305
## [16] {uemp12m=Not unemployed,
## health=Fair health,
## happy=High happiness} => {hincfel=Coping} 0.03552753 0.5334873 0.06659489 1.205259 4628. Visualization of Association Rules
To enhance interpretability, the results are visualized using:
- A support–confidence scatter plot, with lift represented by color intensity
- A network graph, illustrating the relationships between antecedents and income perception outcomes
These visualizations help identify dominant patterns and clusters among the rules.
Support–Confidence plot
plot(
strong_rules,
measure = c("support", "confidence"),
shading = "lift"
)
# Rule network
plot(
strong_rules,
method = "graph",
control = list(type = "items")
)## Available control parameters (with default values):
## layout = stress
## circular = FALSE
## ggraphdots = NULL
## edges = <environment>
## nodes = <environment>
## nodetext = <environment>
## colors = c("#EE0000FF", "#EEEEEEFF")
## engine = ggplot2
## max = 100
## verbose = FALSE
9. Interpretation Strategy
The final step focuses on interpreting the strongest rules in
substantive terms.
Each rule is discussed in relation to socio-economic theory, emphasizing
how education, employment status, health, and well-being relate to
perceived household income adequacy.
10. Conclusion
The association rule analysis provides insights into the combinations
of characteristics that are most frequently associated with different
perceptions of household income across Europe.
The findings complement traditional statistical approaches by uncovering
multi-variable patterns within the survey data.