Database and fieldwork control
Jonathan Rougier
18/05/2021
DATA BASE REVISION
1. Data base structure
We have checked that all the survey’s questions were included in the data base while the categories and codes on the variables correspond to those ones in the questionnaire.
Following our checks, we conclude that the data base does not show problems of inconsistency since all the variables were included. Some questions on people’s perception towards different government institutions required logic skips by country and these were conducted properly. QR located items can be found here and the revision base on the the data outcome here.
When it comes to the categories and codes of each variable, we can observe they follow the questionnaire requirements. However, the level of measuring of some variables should be changed in the database in order to avoid further problems when statistical test are ran in SPSS or other softwares.
## tibble [7,337 x 102] (S3: tbl_df/tbl/data.frame)
## $ ID : num [1:7337] 211 212 213 186 189 190 192 194 196 200 ...
## ..- attr(*, "label")= chr "Resp ID"
## ..- attr(*, "format.spss")= chr "F8.0"
## $ SCREENER_START : chr [1:7337] "2021-02-06 17:11:33" "2021-02-06 17:12:57" "2021-02-06 17:13:00" "2021-02-06 14:37:22" ...
## ..- attr(*, "label")= chr "SCREENER_START"
## ..- attr(*, "format.spss")= chr "A19"
## ..- attr(*, "display_width")= int 19
## $ GENDER : dbl+lbl [1:7337] 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## ..@ label : chr "GENDER"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:2] 1 2
## .. ..- attr(*, "names")= chr [1:2] "Male interviewer" "Female interviewer"
## $ COUNTRY : dbl+lbl [1:7337] 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,...
## ..@ label : chr "COUNTRY"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:17] 1 2 3 4 5 6 7 8 9 10 ...
## .. ..- attr(*, "names")= chr [1:17] "PNG" "Fiji" "Solomon Islands" "New Caledonia" ...
## $ InterviewerID : dbl+lbl [1:7337] 9, 19, 18, 16, 9, 18, 19, 8, 16, 19, 8, 12, 12, 1...
## ..@ label : chr "Interviewer ID"
## ..@ format.spss: chr "F3.0"
## ..@ labels : Named num [1:127] 1 2 3 4 5 6 7 8 9 10 ...
## .. ..- attr(*, "names")= chr [1:127] "CK210305" "CK210301" "CK210310" "CK210306" ...
## $ SSU : dbl+lbl [1:7337] 20100, 20300, 20100, 20100, 20100, 20300, 20300, 2020...
## ..@ label : chr "TestScreen for SSU"
## ..@ format.spss: chr "F6.0"
## ..@ labels : Named num [1:299] 10100 10200 10300 10400 10500 10600 10700 10800 10900 11000 ...
## .. ..- attr(*, "names")= chr [1:299] "AR Bougainville" "Central" "Chimbu" "East New Britain" ...
## $ PHONETYPE : dbl+lbl [1:7337] 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1,...
## ..@ label : chr "PHONETYPE"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:2] 1 2
## .. ..- attr(*, "names")= chr [1:2] "Mobile phone" "Landline"
## $ LANG : dbl+lbl [1:7337] 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 1, 1, 4, 1, 1, 1, 1, 4,...
## ..@ label : chr "Language"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:10] 1 2 3 4 5 6 7 8 9 10
## .. ..- attr(*, "names")= chr [1:10] "English" "Tok pisin" "Fijian" "Fiji Hindi" ...
## $ SC1 : dbl+lbl [1:7337] 2, NA, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2, N...
## ..@ label : chr "Mobile number shared"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:2] 1 2
## .. ..- attr(*, "names")= chr [1:2] "Yes" "No"
## $ SC2 : dbl+lbl [1:7337] NA, 1, NA, NA, 1, NA, NA, NA, NA, 1, NA, NA, NA, ...
## ..@ label : chr "Help selection"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:2] 1 2
## .. ..- attr(*, "names")= chr [1:2] "Yes" "No"
## $ SC4 : num [1:7337] NA 4 NA NA 7 NA NA NA NA 5 ...
## ..- attr(*, "label")= chr "Count aged 18 or more"
## ..- attr(*, "format.spss")= chr "F2.0"
## $ SC5 : dbl+lbl [1:7337] NA, 1, NA, NA, 1, NA, NA, NA, NA, 1, NA, NA, NA, ...
## ..@ label : chr "Last birthday available"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:3] 1 2 3
## .. ..- attr(*, "names")= chr [1:3] "Yes, it is the person on the phone" "Yes, the respondent is calling another member of the household" "No, eligible respondent is not currently available"
## $ SC6 : dbl+lbl [1:7337] 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
## ..@ label : chr "OK TO PROCEED"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:188] 1 101 102 103 104 105 106 107 108 109 ...
## .. ..- attr(*, "names")= chr [1:188] "OK TO PROCEED" "AR Bougainville" "Central" "Chimbu" ...
## $ SC7 : dbl+lbl [1:7337] 201, 203, 201, 201, 201, 203, 203, 202, 201, 207, 201...
## ..@ label : chr "Region"
## ..@ format.spss: chr "F4.0"
## ..@ labels : Named num [1:188] 1 101 102 103 104 105 106 107 108 109 ...
## .. ..- attr(*, "names")= chr [1:188] "OK TO PROCEED" "AR Bougainville" "Central" "Chimbu" ...
## $ SC8 : num [1:7337] 28 21 30 28 29 30 31 23 27 28 ...
## ..- attr(*, "label")= chr "How old are you?"
## ..- attr(*, "format.spss")= chr "F3.0"
## $ SC10 : dbl+lbl [1:7337] 2, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1,...
## ..@ label : chr "What is your gender?"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:2] 1 2
## .. ..- attr(*, "names")= chr [1:2] "Male" "Female"
## $ Q1a_1 : dbl+lbl [1:7337] 3, 2, 2, 3, 4, 3, 2, 4, 1, 3, 3, 3, 2, 3, 4, 2, 4, 3,...
## ..@ label : chr "Country confidence : The government (including politicians, public servants or any kind of government agency)"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "No trust at all" "Not very much trust" "A fair amount of trust" "A great deal of trust" ...
## $ SCREENER_END : chr [1:7337] "2021-02-06 17:15:49" "2021-02-06 17:20:10" "2021-02-06 17:15:56" "2021-02-06 14:40:28" ...
## ..- attr(*, "label")= chr "SCREENER_END"
## ..- attr(*, "format.spss")= chr "A19"
## ..- attr(*, "display_width")= int 19
## $ SECTION_A_START : chr [1:7337] "2021-02-06 17:15:49" "2021-02-06 17:20:10" "2021-02-06 17:15:56" "2021-02-06 14:40:28" ...
## ..- attr(*, "label")= chr "SECTION_A_START"
## ..- attr(*, "format.spss")= chr "A19"
## ..- attr(*, "display_width")= int 19
## $ Q1a_2 : dbl+lbl [1:7337] 3, 3, 1, 4, 3, 3, 2, 3, 3, 4, 3, 3, 3, 3, 3, 4, 3, 3,...
## ..@ label : chr "Country confidence : The courts"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "No trust at all" "Not very much trust" "A fair amount of trust" "A great deal of trust" ...
## $ Q1a_3 : dbl+lbl [1:7337] 3, 2, 3, 3, 4, 3, 2, 4, 1, 3, 3, 3, 4, 3, 4, 3, 4, 4,...
## ..@ label : chr "Country confidence : The police"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "No trust at all" "Not very much trust" "A fair amount of trust" "A great deal of trust" ...
## $ Q1a_4 : dbl+lbl [1:7337] 3, 2, 2, 3, 4, 3, 2, 3, 3, 4, 3, 3, 3, 3, 3, 3, 3, 1,...
## ..@ label : chr "Country confidence : Business that provides services for the government"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "No trust at all" "Not very much trust" "A fair amount of trust" "A great deal of trust" ...
## $ Q1a_5 : dbl+lbl [1:7337] 2, 2, 3, 4, 4, 3, 2, 4, 3, 3, 3, 3, 3, 3, 4, 3, 4, 3,...
## ..@ label : chr "Country confidence : The military"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "No trust at all" "Not very much trust" "A fair amount of trust" "A great deal of trust" ...
## $ Q1a_6 : dbl+lbl [1:7337] 4, 2, 3, 2, 4, 4, 3, 4, 4, 3, 4, 3, 4, 3, 4, 3, 4, 3,...
## ..@ label : chr "Country confidence : The banks"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "No trust at all" "Not very much trust" "A fair amount of trust" "A great deal of trust" ...
## $ Q1a_7 : dbl+lbl [1:7337] 3, 4, 2, 4, 4, 3, 3, 4, 3, 4, 3, 3, 4, 3, 4, 4, 4, 1,...
## ..@ label : chr "Country confidence : Religious institutions"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "No trust at all" "Not very much trust" "A fair amount of trust" "A great deal of trust" ...
## $ Q1a_8 : dbl+lbl [1:7337] 3, 2, 5, 3, 4, 3, 3, 4, 3, 4, 3, 3, 3, 3, 3, 3, 3, 3,...
## ..@ label : chr "Country confidence : Civil society organisations"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "No trust at all" "Not very much trust" "A fair amount of trust" "A great deal of trust" ...
## $ Q1a_9 : dbl+lbl [1:7337] 3, 3, 2, 3, 4, 3, 3, 4, 4, 4, 3, 3, 3, 1, 4, 3, 3, 1,...
## ..@ label : chr "Country confidence : Local community"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "No trust at all" "Not very much trust" "A fair amount of trust" "A great deal of trust" ...
## $ Q2a : dbl+lbl [1:7337] 3, 4, 2, 3, 2, 1, 4, 1, 4, 3, 3, 2, 4, 2, 4, 4, 2, 2,...
## ..@ label : chr "Country corruption"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:5] 1 2 3 4 99
## .. ..- attr(*, "names")= chr [1:5] "No problem at all" "Fairly small" "Fairly big" "A very big problem" ...
## $ Q2b : dbl+lbl [1:7337] 2, 1, 3, 99, 2, 1, 99, 3, 1, 3, 99, 3, 3, ...
## ..@ label : chr "Business sector corruption"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:5] 1 2 3 4 99
## .. ..- attr(*, "names")= chr [1:5] "No problem at all" "Fairly small" "Fairly big" "A very big problem" ...
## $ Q4_1 : dbl+lbl [1:7337] 4, 4, 3, 3, 1, 3, 4, 2, 4, 99, 3, 3, 4, ...
## ..@ label : chr "Change in corruption : Government"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Decreased a lot" "Somewhat decreased" "Stayed the same" "Somewhat increased" ...
## $ Q4_2 : dbl+lbl [1:7337] 4, 4, 99, 99, 1, 3, 99, 4, 5, 99, 3, 4, 3, ...
## ..@ label : chr "Change in corruption : Business sector"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Decreased a lot" "Somewhat decreased" "Stayed the same" "Somewhat increased" ...
## $ Q5 : dbl+lbl [1:7337] 2, 4, 4, 99, 4, 2, 1, 5, 4, 4, 4, 4, 4, ...
## ..@ label : chr "Government fighting corruption"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:5] 1 2 4 5 99
## .. ..- attr(*, "names")= chr [1:5] "Very badly" "Fairly badly" "Fairly well" "Very well" ...
## $ Q6_1 : dbl+lbl [1:7337] 2, 3, 2, 5, 1, 2, 5, 1, 2, 3, 2, 2, 5, 1, 2, 2, 2, 1,...
## ..@ label : chr "People involved in corruption : The President and Officials in his/her Office"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_2 : dbl+lbl [1:7337] 2, 3, 2, 5, 1, 2, 5, 1, 2, 3, 2, 2, 5, 1, 1, 2, 2, 5,...
## ..@ label : chr "People involved in corruption : The Prime Minister and Officials in his/her Office"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_3 : dbl+lbl [1:7337] 2, 3, 2, 5, 1, 2, 2, 2, 2, 3, 2, 2, 5, 2, 2, 2, 3, 4,...
## ..@ label : chr "People involved in corruption : Members of Parliament"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_4 : dbl+lbl [1:7337] 2, 4, 2, 5, 1, 2, 2, 2, 3, 3, 2, 2, 2, 2, 1, 3, 2, 5,...
## ..@ label : chr "People involved in corruption : Public servants or civil servants"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_5 : dbl+lbl [1:7337] 5, 4, 2, 5, 1, 2, 5, 2, 2, 3, 2, 2, 2, 2, 1, 3, 1, 5,...
## ..@ label : chr "People involved in corruption : Local Government Mayor"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_6 : dbl+lbl [1:7337] 2, 4, 3, 5, 1, 2, 2, 1, 2, 3, 2, 2, 2, 3, 1, 2, 1, 2,...
## ..@ label : chr "People involved in corruption : Police"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_7 : dbl+lbl [1:7337] 1, 4, 2, 5, 1, 2, 5, 1, 2, 1, 2, 2, 2, 1, 1, 2, 1, 4,...
## ..@ label : chr "People involved in corruption : Judges and Magistrates"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_8 : dbl+lbl [1:7337] 1, 1, 2, 5, 1, 2, 5, 1, 3, 1, 2, 2, 2, 1, 2, 1, 2, 2,...
## ..@ label : chr "People involved in corruption : Religious leaders"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_9 : dbl+lbl [1:7337] 2, 3, 2, 4, 2, 2, 2, 2, 2, 3, 2, 2, 2, 1, 2, 3, 2, 2,...
## ..@ label : chr "People involved in corruption : Business executives"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_10 : dbl+lbl [1:7337] 5, 3, 2, 5, 2, 2, 2, 2, 2, 3, 2, 2, 5, 3, 1, 3, 2, 3,...
## ..@ label : chr "People involved in corruption : Workers in civil society organisations"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_11 : dbl+lbl [1:7337] 1, 2, 2, 4, 1, 2, 5, 2, 2, 1, 1, 2, 1, 1, 2, 1, 2, 2,...
## ..@ label : chr "People involved in corruption : Bankers"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_12 : dbl+lbl [1:7337] 2, 2, 2, 5, 1, 2, 5, 1, 3, 1, 2, 2, 1, 1, 1, 3, 5, 4,...
## ..@ label : chr "People involved in corruption : Military Leaders"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_13 : dbl+lbl [1:7337] 1, 2, 2, 5, 1, 2, 5, 1, 2, 3, 2, 2, 5, 1, 2, 2, 3, 1,...
## ..@ label : chr "People involved in corruption : Companies extracting national resources"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q6_14 : dbl+lbl [1:7337] 2, 2, 2, 5, 1, 2, 5, 2, 2, 3, 2, 2, 2, 3, 2, 2, 2, 3,...
## ..@ label : chr "People involved in corruption : Community leaders"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "None" "Some of them" "Most of them" "All of them" ...
## $ Q8_1 : dbl+lbl [1:7337] 2, 2, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2, ...
## ..@ label : chr "Services contact : A public school"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:3] 1 2 99
## .. ..- attr(*, "names")= chr [1:3] "YES" "NO" "Don’t know"
## $ SECTION_A_END : chr [1:7337] "2021-02-06 17:24:03" "2021-02-06 17:24:37" "2021-02-06 17:22:13" "2021-02-06 14:50:13" ...
## ..- attr(*, "label")= chr "SECTION_A_END"
## ..- attr(*, "format.spss")= chr "A19"
## ..- attr(*, "display_width")= int 19
## $ SECTION_B_START : chr [1:7337] "2021-02-06 17:24:03" "2021-02-06 17:24:37" "2021-02-06 17:22:13" "2021-02-06 14:50:13" ...
## ..- attr(*, "label")= chr "SECTION_B_START"
## ..- attr(*, "format.spss")= chr "A19"
## ..- attr(*, "display_width")= int 19
## $ Q8_2 : dbl+lbl [1:7337] 1, 2, 2, 1, 2, 2, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 2, 2,...
## ..@ label : chr "Services contact : A public clinic or hospital"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:3] 1 2 99
## .. ..- attr(*, "names")= chr [1:3] "YES" "NO" "Don’t know"
## $ Q8_3 : dbl+lbl [1:7337] 2, 1, 2, 2, 1, 1, 2, 1, 1, 1, 2, 1, 1, ...
## ..@ label : chr "Services contact : Government office to get an identity document like a birth certificate, drivers license, pas"| __truncated__
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:3] 1 2 99
## .. ..- attr(*, "names")= chr [1:3] "YES" "NO" "Don’t know"
## $ Q8_4 : dbl+lbl [1:7337] 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 2, 2, 2, ...
## ..@ label : chr "Services contact : Governments service provider to get water, sanitation or electric services"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:3] 1 2 99
## .. ..- attr(*, "names")= chr [1:3] "YES" "NO" "Don’t know"
## $ Q8_5 : dbl+lbl [1:7337] 2, 2, 2, 2, 1, 2, 2, 2, 1, 2, 2, 2, 2, ...
## ..@ label : chr "Services contact : The police"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:3] 1 2 99
## .. ..- attr(*, "names")= chr [1:3] "YES" "NO" "Don’t know"
## $ Q8_6 : dbl+lbl [1:7337] 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2,...
## ..@ label : chr "Services contact : The courts"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:3] 1 2 99
## .. ..- attr(*, "names")= chr [1:3] "YES" "NO" "Don’t know"
## $ Q10_1 : dbl+lbl [1:7337] NA, NA, NA, NA, 1, NA, NA, NA, NA, 1, NA, NA, NA, ...
## ..@ label : chr "Services favours : A public school"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q10_2 : dbl+lbl [1:7337] 1, NA, NA, 99, NA, NA, 1, 1, 1, 1, 1, NA, NA, ...
## ..@ label : chr "Services favours : A public clinic or hospital"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q10_3 : dbl+lbl [1:7337] NA, 1, NA, NA, 1, 1, NA, 1, 2, 1, NA, 1, 1, ...
## ..@ label : chr "Services favours : Government office in order to get the document you needed"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q10_4 : dbl+lbl [1:7337] NA, 1, NA, NA, 3, NA, 1, 1, 1, 1, NA, NA, NA, N...
## ..@ label : chr "Services favours : Governments service provider to get water, sanitation or electric services"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q10_5 : dbl+lbl [1:7337] NA, NA, NA, NA, 2, NA, NA, NA, 1, NA, NA, NA, NA, N...
## ..@ label : chr "Services favours : The police"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q10_6 : dbl+lbl [1:7337] NA, NA, NA, NA, 2, NA, NA, NA, NA, NA, NA, NA, NA, N...
## ..@ label : chr "Services favours : The courts"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q21a : dbl+lbl [1:7337] NA, NA, NA, NA, 2, NA, NA, NA, 1, NA, NA, NA, NA, ...
## ..@ label : chr "Reason for favours"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "I would have not received the service without my personal connection" "I wanted to get a quicker service than what is usually offered" "I wanted to get a better service than what is usually offered" "It was a way to help each other" ...
## $ Q9_1 : dbl+lbl [1:7337] NA, NA, NA, NA, 3, NA, NA, NA, NA, 1, NA, NA, NA, ...
## ..@ label : chr "Services bribe : A public school"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q9_2 : dbl+lbl [1:7337] 1, NA, NA, 1, NA, NA, 1, 1, 2, 1, 1, NA, NA, ...
## ..@ label : chr "Services bribe : A public clinic or hospital"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q9_3 : dbl+lbl [1:7337] NA, 1, NA, NA, 1, 1, NA, 1, 1, 1, NA, 1, 1, ...
## ..@ label : chr "Services bribe : Government office in order to get the document you needed"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q9_4 : dbl+lbl [1:7337] NA, 1, NA, NA, 2, NA, 1, 1, 1, 1, NA, NA, NA, N...
## ..@ label : chr "Services bribe : Governments service provider to get water, sanitation or electric services"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q9_5 : dbl+lbl [1:7337] NA, NA, NA, NA, 2, NA, NA, NA, 1, NA, NA, NA, NA, N...
## ..@ label : chr "Services bribe : The police"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q9_6 : dbl+lbl [1:7337] NA, NA, NA, NA, 1, NA, NA, NA, NA, NA, NA, NA, NA, N...
## ..@ label : chr "Services bribe : The courts"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q14a : dbl+lbl [1:7337] NA, NA, NA, NA, 4, NA, NA, NA, 4, NA, NA, NA, NA, N...
## ..@ label : chr "Bribe reason"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:9] 1 2 3 4 5 6 7 98 99
## .. ..- attr(*, "names")= chr [1:9] "You were asked to pay" "You were not asked to pay but you knew it was expected" "You offered to pay to get things done quicker" "You offered to pay to get things done better" ...
## $ Q14b : dbl+lbl [1:7337] NA, NA, NA, NA, 2, NA, NA, NA, 2, NA, NA, NA, NA, N...
## ..@ label : chr "Report bribe"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:3] 1 2 99
## .. ..- attr(*, "names")= chr [1:3] "Yes" "No" "Don’t know"
## $ Q17 : dbl+lbl [1:7337] 3, 3, 3, 2, 3, 2, 3, 3, 3, 1, 1, 3, 1, ...
## ..@ label : chr "Overall country sexual requests"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:7] 1 2 3 4 5 98 99
## .. ..- attr(*, "names")= chr [1:7] "Never" "Rarely" "Occasionally" "Often" ...
## $ Q18 : dbl+lbl [1:7337] 1, 1, 1, 1, 1, 1, 2, 1, 2, 1, 1, 1, 1, ...
## ..@ label : chr "Personal country sexual requests"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 98 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Once or twice" "A few times" "Often" ...
## $ Q19b : dbl+lbl [1:7337] 1, 1, 1, 1, 1, 99, 3, 1, 1, 1, 1, 1, 1, ...
## ..@ label : chr "Personal election bribe"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:7] 1 2 3 4 97 98 99
## .. ..- attr(*, "names")= chr [1:7] "Never" "Once or twice" "A few times" "Often" ...
## $ Q19c : dbl+lbl [1:7337] 1, 1, 1, 1, 1, 99, 3, 1, 1, 1, 1, 1, 1, ...
## ..@ label : chr "Family election bribe"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:7] 1 2 3 4 97 98 99
## .. ..- attr(*, "names")= chr [1:7] "Never" "Once or twice" "A few times" "Often" ...
## $ Q20c : dbl+lbl [1:7337] 1, 1, 1, 1, 1, 99, 3, 1, 1, 1, 1, 1, 1, ...
## ..@ label : chr "Personal election threat"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:7] 1 2 3 4 97 98 99
## .. ..- attr(*, "names")= chr [1:7] "Never" "Once or twice" "A few times" "Often" ...
## $ Q22a_1 : dbl+lbl [1:7337] 5, 3, 3, 5, 4, 3, 5, 5, 5, 5, 3, 5, 4, ...
## ..@ label : chr "Corruption thoughts : Ordinary people can make a difference in the fight against corruption"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Strongly disagree" "Tend to disagree" "Neither agree nor disagree" "Tend to agree" ...
## $ SECTION_B_END : chr [1:7337] "2021-02-06 17:28:24" "2021-02-06 17:27:57" "2021-02-06 17:23:53" "2021-02-06 14:54:46" ...
## ..- attr(*, "label")= chr "SECTION_B_END"
## ..- attr(*, "format.spss")= chr "A19"
## ..- attr(*, "display_width")= int 19
## $ SECTION_C_START : chr [1:7337] "2021-02-06 17:24:03" "2021-02-06 17:24:37" "2021-02-06 17:22:13" "2021-02-06 14:50:13" ...
## ..- attr(*, "label")= chr "SECTION_C_START"
## ..- attr(*, "format.spss")= chr "A19"
## ..- attr(*, "display_width")= int 19
## $ Q22a_2 : dbl+lbl [1:7337] 1, 2, 1, 99, 2, 3, 1, 1, 4, 2, 2, 1, 1, ...
## ..@ label : chr "Corruption thoughts : It is acceptable for the government to engage in a bit of corruption as long as it delivers good results"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Strongly disagree" "Tend to disagree" "Neither agree nor disagree" "Tend to agree" ...
## $ Q22a_3 : dbl+lbl [1:7337] 1, 4, 1, 1, 4, 4, 1, 1, 4, 1, 3, 1, 1, ...
## ..@ label : chr "Corruption thoughts : If someone in a position of responsibility helps me, then I feel I should give them a gif"| __truncated__
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Strongly disagree" "Tend to disagree" "Neither agree nor disagree" "Tend to agree" ...
## $ Q22a_4 : dbl+lbl [1:7337] 4, 5, 4, 5, 4, 4, 5, 5, 4, 5, 2, 3, 4, ...
## ..@ label : chr "Corruption thoughts : There is little control over those who exploit our natural resources"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Strongly disagree" "Tend to disagree" "Neither agree nor disagree" "Tend to agree" ...
## $ Q22a_5 : dbl+lbl [1:7337] 5, 3, 3, 1, 4, 4, 3, 5, 4, 3, 5, 3, 5, 5, 1, 5, 5, 5,...
## ..@ label : chr "Corruption thoughts : The government in [COUNTRY] has been transparent in its handling of the COVID-19 pandemic"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Strongly disagree" "Tend to disagree" "Neither agree nor disagree" "Tend to agree" ...
## $ Q24_1 : dbl+lbl [1:7337] 3, 3, 4, 4, 3, 2, 99, 2, 3, 5, 3, 2, 2, ...
## ..@ label : chr "Corruption thoughts continued : People using their personal or political connections to get a better service fr"| __truncated__
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Rarely" "Occasionally" "Frequently" ...
## $ Q24_2 : dbl+lbl [1:7337] 3, 5, 4, 4, 3, 2, 3, 3, 2, 3, 3, 2, 2, ...
## ..@ label : chr "Corruption thoughts continued : Companies using money or connections to secure profitable government contracts"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Rarely" "Occasionally" "Frequently" ...
## $ Q24_3 : dbl+lbl [1:7337] 4, 4, 5, 4, 3, 2, 3, 2, 3, 3, 2, 5, 1, ...
## ..@ label : chr "Corruption thoughts continued : A public servant influencing a hiring decision in their department to favour a "| __truncated__
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Rarely" "Occasionally" "Frequently" ...
## $ Q24_4 : dbl+lbl [1:7337] 5, 5, 4, 1, 3, 2, 5, 3, 4, 3, 3, 3, 4, ...
## ..@ label : chr "Corruption thoughts continued : Officials who engage in corruption face appropriate action against them"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Rarely" "Occasionally" "Frequently" ...
## $ Q24_5 : dbl+lbl [1:7337] 3, 4, 3, 99, 3, 2, 4, 2, 4, 5, 3, 99, 4, ...
## ..@ label : chr "Corruption thoughts continued : The Government in [COUNTRY] is pretty much run by a few big interests looking o"| __truncated__
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Rarely" "Occasionally" "Frequently" ...
## $ Q24_6 : dbl+lbl [1:7337] 3, 5, 5, 99, 3, 2, 99, 3, 1, 99, 4, 4, 2, ...
## ..@ label : chr "Corruption thoughts continued : Big companies avoid to pay their taxes."
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Rarely" "Occasionally" "Frequently" ...
## $ Q24_7 : dbl+lbl [1:7337] 3, 2, 2, 2, 3, 1, 1, 3, 2, 3, 3, 2, 1, ...
## ..@ label : chr "Corruption thoughts continued : The government in [COUNTRY] takes the views of people like me into account when"| __truncated__
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 99
## .. ..- attr(*, "names")= chr [1:6] "Never" "Rarely" "Occasionally" "Frequently" ...
## $ Q21 : dbl+lbl [1:7337] 5, 5, 5, 6, 6, 5, 5, 5, 6, 6, 4, 5, 5, 6, 2, 5, 6, 6,...
## ..@ label : chr "Inform on public affairs"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:8] 1 2 3 4 5 6 98 99
## .. ..- attr(*, "names")= chr [1:8] "Not at all" "Less often" "At least once a month" "At least once a week" ...
## $ SECTION_C_END : chr [1:7337] "2021-02-06 17:28:06" "2021-02-06 17:27:46" "2021-02-06 17:24:08" "2021-02-06 14:53:58" ...
## ..- attr(*, "label")= chr "SECTION_C_END"
## ..- attr(*, "format.spss")= chr "A19"
## ..- attr(*, "display_width")= int 19
## $ SECTION_D_START : chr [1:7337] "2021-02-06 17:28:06" "2021-02-06 17:27:46" "2021-02-06 17:24:08" "2021-02-06 14:53:58" ...
## ..- attr(*, "label")= chr "SECTION_D_START"
## ..- attr(*, "format.spss")= chr "A19"
## ..- attr(*, "display_width")= int 19
## $ Q22 : dbl+lbl [1:7337] 1, 1, 2, 2, 3, 4, 5, 1, 2, 3, 1, 2, 3, 2, 1, 5, 3, 4,...
## ..@ label : chr "Source of information for public affairs"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:7] 1 2 3 4 5 98 99
## .. ..- attr(*, "names")= chr [1:7] "Facebook or other social media" "TV news" "Radio" "Online media, such as Google news" ...
## $ Q26 : dbl+lbl [1:7337] 5, 6, 7, 3, 2, 1, 1, 1, 7, 5, 1, 2, 7, ...
## ..@ label : chr "Working status"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:9] 1 2 3 4 5 6 7 98 99
## .. ..- attr(*, "names")= chr [1:9] "Working full-time (more than 30 hours per week)" "Working part-time (less than 30 hours per week)" "Not working and looking for work" "Retired" ...
## $ Q27 : dbl+lbl [1:7337] NA, NA, NA, NA, 16, 15, 18, 10, NA, NA, 3, 1, NA, N...
## ..@ label : chr "Occupation"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:25] 1 2 3 4 5 6 7 8 9 10 ...
## .. ..- attr(*, "names")= chr [1:25] "Subsistence farmer (produces only for home consumption)" "Peasant Farmer or Small scale producer (produces both for own consumption and some surplus produce for sale)" "Commercial Farmer (produces mainly for sale)" "Farm worker" ...
## $ Q28 : dbl+lbl [1:7337] 23, 0, 0, 23, NA, NA, NA, NA, 23, 0, NA, NA, 0, 1...
## ..@ label : chr "Last main occupation"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:26] 0 1 2 3 4 5 6 7 8 9 ...
## .. ..- attr(*, "names")= chr [1:26] "Never had a job" "Subsistence farmer (produces only for home consumption)" "Peasant Farmer or Small scale producer (produces both for own consumption and some surplus produce for sale)" "Commercial Farmer (produces mainly for sale)" ...
## $ Q29 : dbl+lbl [1:7337] 9, 11, 4, 7, 6, 10, 7, 5, 7, 11, 5, 4, 11, ...
## ..@ label : chr "Education"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:13] 0 1 2 3 4 5 6 7 8 9 ...
## .. ..- attr(*, "names")= chr [1:13] "No formal education" "Informal schooling only" "Some primary schooling" "Primary school completed" ...
## $ Q30 : dbl+lbl [1:7337] 3, 3, 4, 4, 2, 3, 4, 4, 1, 4, 3, 4, 2, ...
## ..@ label : chr "Household income"
## ..@ format.spss: chr "F2.0"
## ..@ labels : Named num [1:6] 1 2 3 4 5 98
## .. ..- attr(*, "names")= chr [1:6] "We can’t buy at all what we need, we have no savings or no income" "We need to borrow or spend savings to buy things we need" "We can manage with difficulties" "We have just enough to buy what is needed" ...
## $ Q36 : dbl+lbl [1:7337] 3, 1, 4, 2, 4, 2, 1, 1, 4, 3, 4, 3, 5, 1, 3, 2, 3, 3,...
## ..@ label : chr "Area description"
## ..@ format.spss: chr "F1.0"
## ..@ labels : Named num [1:5] 1 2 3 4 5
## .. ..- attr(*, "names")= chr [1:5] "A big city or the main city" "The outer suburbs or outskirts of a big city" "A town or a small city" "A rural area, rural village, rural settlement" ...
## $ SECTION_D_END : chr [1:7337] "2021-02-06 17:32:12" "2021-02-06 17:29:57" "2021-02-06 17:29:18" "2021-02-06 14:57:54" ...
## ..- attr(*, "label")= chr "SECTION_D_END"
## ..- attr(*, "format.spss")= chr "A19"
## ..- attr(*, "display_width")= int 19
## [list output truncated]In order to polish the data base structure, we must conduct the follwing changes:
SC6: This variable is overlapping with SC7. It contains a code to proceed with the interview, which corresponds to SC6, and at the same time, the codes for region from SC7. Please revise. Check as well level of measurement, it should be “Nominal”.
SC7: Same overlapping as SC6. We should keep just one of these variables.
Q1a_1 to Q1a_9: We have to fix the level of mesurement. Plase, change level of measurement to “Ordinal”.
Q2a to Q2b: We have to fix the level of mesurement. Plase, change level of measurement to “Ordinal”.
Q4_1 to Q4_2: We have to fix the level of mesurement. Plase,change level of measurement to “Ordinal”.
Q5: We have to fix the level of mesurement. Plase, change level of measurement to “Ordinal”.
Q6_1 to Q6_14: We have to fix the level of mesurement. Plase,change level of measurement to “Ordinal”.
Q10_1 to Q10_6: We have to fix the level of mesurement. Plase, change level of measurement to “Ordinal”.
Q9_1 to Q9_6: We have to fix the level of mesurement. Plase,change level of measurement to “Ordinal”.
Q17: We have to fix the level of mesurement. Plase, change level of measurement to “Ordinal”.
Q18: We have to fix the level of mesurement. Plase,change level of measurement to “Ordinal”.
Q19b: We have to fix the level of mesurement. Plase, change level of measurement to “Ordinal”.
Q19c: We have to fix the level of mesurement. Plase, change level of measurement to “Ordinal”.
Q20c: We have to fix the level of mesurement. Plase, change level of measurement to “Ordinal”.
Q22a_1 to Q22a_5: We have to fix the level of mesurement. Plase,change level of measurement to “Ordinal”.
Q24_1 to Q24_7: We have to fix the level of mesurement. Plase, change level of measurement to “Ordinal”.
Q21: We have to fix the level of mesurement. Plase, change level of measurement to “Ordinal”.
Q30: We have to fix the level of mesurement. Plase, change level of measurement to “Ordinal”.
2. Sampling achieved.
The sampling method proposed was telephone interviews with interlocked quota control by gender, age and region. We contrasted the sample achieved against the proposed sample following the inter-lock quota. As well as the samples obtained were checked against the available population parameters.
We could observe that the samples achieved follow the proposed interlock quotas for gender, age and region in the 17 countries, although small skews have been observed in some markets.
Below we describe the samples obtained by market and their profile at national level:
PNG: The total sample accounts for 1025 cases. The sample follows the proposed quota by gender, age and region. At national level, the sample profile is skewed to urban areas.
Fiji: The total sample accounts for 1029 cases. The sample follows the proposed quota by gender, age and region. At national level, the sample profile is skewed to youngest.
Solomon Islands: The total sample accounts for 529 cases. The sample follows the proposed quota by gender, age and region. At national level, the sample is skewed towards urban areas.
New Caledonia: The total sample accounts for 503 cases. The sample follows the proposed quota by gender, age and region, although it is missing 4 respondents for the quota of male between 18 and 30 years old and in “Sud”. At national level, the sample is skewed towards to youngest and some regions in particular.
Vanuatu: The total sample accounts for 516 cases. The sample follows the proposed quota by gender, age and region, although it is missing 4 respondents for the quota of female between 18 and 29 years old. At national level, the sample is skewed towards to urban areas.
French Polynesia: The total sample accounts for 511 interviews. The sample follows the proposed quota by gender, age and region. At national level, the sample is skewed to rural areas. It worth to double-check the distribution of the AREA variable since it is an atypical sort of bias when we conduct telephone sampling.
Samoa: The total sample accounts for 515 interviews. The sample follows the proposed quota by gender, age and region.At national level, the sample is skewed towards to urban areas and some regions in particular.
Tonga: The total sample accounts for 504 interviews. See quotas for Ha’apai region. At national level, the sample is strongly skewed to urban areas and some regions in particular.
Cook Islands: The total sample accounts for 278 interviews. The sample is missing 8 cases in Akaoa-Betela, 5 cases in Matavera and 7 cases in Takuvaine. At national level, the sample is skewed towards to some ranges of age and slightly to urban areas.
Tuvalu: The total sample accounts for 160 interviews. The sample follows the proposed quota by gender, age and region. At national level, the sample is skewed towards to some ages in particular, as well as to urban areas.
Niue: The total sample accounts for 78 interviews. The sample follows the proposed quota by gender, age and region. At national level, the sample presents small skews on some variables due to the sample size.
FSM: The total sample accounts for 507 interviews. The sample follows the proposed quota by gender, age and region.At national level, the sample is strongly skewed towards to urban areas.
Kiribati: The total sample accounts for 507 interviews. See respondents Kiritimati, Banaba (Ocean Island) and Kuria. At national level, the sample is skewed towards to urban areas and people between 35-44 years old.
Marshall Islands: The total sample accounts for 261 cases. The sample follows the proposed quota by gender, age and region, although “other location” are represented mainly by Jaluit. At national level, the sample is skewed towards to some ages in particular and to rural areas. It worth to double-check the distribution of the AREA variable since it is an atypical sort of bias when we conduct telephone sampling.
Palau: The total sample accounts for 255 cases. The sample follows the proposed quota by gender, age and region. At national level, the sample is skewed towards rural areas and some particular ages and regions.
Nauru: The total sample accounts for 101 interviews. The sample follows the proposed quota by gender, age and region.
3.Levels of missings, do not know and no answer by market.
The levels of non-response account for important characteristics about the survey and the questionnaire. Non-response can be understood in multiple ways ranging from the comprehension of the question, the knowledge of the respondent, the degree of commitment to the exercise, the empathy created between the interviewer and the respondent as well as the quality of the data collected.
While the presence of non-response can be understood as a finding in some cases, its systematic repetition and high values may indicate problems in the collection instrument, as well as the interviewer’s lack of empathy and skills in conducting the interview.
In the previous data quality check, high levels of non-response have been found for several markets and were reported to the service provider. In this final check, a pattern of high non-response values can be observed in almost all markets, in some cases reaching worrying levels in questions referring to perceptions or skills that should not present such levels.
The detail regarding the observation by country can be found in the following link We detail below the markets with some concerning levels of “Do not Know” or “No answer”.
Fiji: There are high levels of Do not know (>10%) answers in 22 out of the 64 questions variables.
New Caledonia: There are high levels of Do not know (>10%) responses in 38 out of the 64 questions variables.
Vanuatu: There are high levels of Do not know (>10%) responses in 13 out of the 64 questions variables.
French Polynesia: There are high levels of Do not know (>10%) responses in 21 out of the 64 questions variables.
Samoa: There are high levels of Do not know (>10%) responses in 23 out of the 64 questions variables.
Tonga: There is not a high level of Do not know (>10%) responses in 2 out of the 64 variables.
Cook Islands: There are high levels of Do not know (>10%) responses in 21 out of the 64 variables.
Tuvalu: There are high levels of Do not know (>10%) responses in 7 out of the 64 variables.
Niue: There are high levels of Do not know (>10%) responses in 12 out of the 64 variables.
Tokelau: There are high levels of Do not know (>10%) responses in 28 out of the 64 variables.
Kiribati: There are high levels of Do not know (>10%) responses in 17 out of the 64 variables.
Marshall Islands: There are high levels of Do not know (>10%) responses in 14 out of the 64 variables.
Palau: There are high levels of Do not know (>10%) responses in 15 out of the 64 variables.
Nauru: There are high levels of Do not know (>10%) responses in 37 out of the 64 variables.
4. Length of interview.
The survey was quoted for a questionnaire duration of between 15 and 20 minutes. Reviewing the average, maximum and minimum length of the interview in each market allows us to understand how efficiently and carefully the fieldwork was carried out.
Extremely short interview durations may indicate a lack of commitment on the respondent answers, as well as a lack of commitment on interviewer’s end to follow the questionnaire’s instructions properly.
On the other hand, surveys whose lengths are much longer than average may indicate a lack of respondent comprehension. According to the literature on the topic, the interviewees’ attention thresholds are between 8 and 15 minutes for CATI interviews.Some specialists speak of attention thresholds that, once exceeded, increase fatigue and the quality of the response.
Below are displayed the average, minimum, maximum LOI. As well as the duration for the first quantile and third quantile of the sample.
| COUNTRY | mean_LOI | median_LOI | minimum_LOI | maximum_LOI | quantile_25 | quantile_75 | total_sample |
|---|---|---|---|---|---|---|---|
| PNG | 00:15:32 | 00:14:46 | 00:04:48 | 00:40:03 | 00:11:53 | 00:18:20 | 1025 |
| Fiji | 00:14:55 | 00:14:20 | 00:03:48 | 00:43:44 | 00:11:24 | 00:17:39 | 1029 |
| Solomon Islands | 00:22:09 | 00:21:12 | 00:07:41 | 00:47:09 | 00:17:35 | 00:25:49 | 529 |
| New Caledonia | 00:10:58 | 00:09:56 | 00:05:00 | 00:35:35 | 00:07:23 | 00:13:14 | 503 |
| Vanuatu | 00:18:12 | 00:17:39 | 00:05:12 | 00:49:54 | 00:13:03 | 00:22:36 | 516 |
| French Polynesia | 00:13:27 | 00:11:33 | 00:04:42 | 00:51:45 | 00:08:32 | 00:16:27 | 511 |
| Samoa | 00:14:13 | 00:12:20 | 00:05:01 | 01:13:20 | 00:08:53 | 00:17:55 | 515 |
| Tonga | 00:12:16 | 00:10:30 | 00:04:59 | 00:50:40 | 00:08:10 | 00:15:25 | 504 |
| Cook Islands | 00:13:15 | 00:11:07 | 00:04:40 | 00:41:15 | 00:08:33 | 00:15:55 | 279 |
| Tuvalu | 00:15:24 | 00:12:43 | 00:05:31 | 01:02:58 | 00:09:50 | 00:17:50 | 160 |
| Niue | 00:18:03 | 00:17:28 | 00:07:09 | 00:43:59 | 00:12:40 | 00:21:33 | 78 |
| Tokelau | 00:09:54 | 00:09:05 | 00:05:09 | 00:23:17 | 00:07:01 | 00:11:01 | 58 |
| FSM | 00:10:30 | 00:07:59 | 00:04:56 | 00:40:28 | 00:06:10 | 00:12:00 | 507 |
| Kiribati | 00:10:11 | 00:08:29 | 00:04:47 | 00:47:20 | 00:06:48 | 00:11:15 | 505 |
| Marshall Islands | 00:12:46 | 00:11:30 | 00:04:25 | 00:37:30 | 00:08:15 | 00:15:53 | 261 |
| Palau | 00:10:42 | 00:08:46 | 00:04:28 | 00:36:51 | 00:07:17 | 00:12:24 | 255 |
| Nauru | 00:11:52 | 00:10:52 | 00:05:32 | 00:30:58 | 00:08:45 | 00:13:27 | 101 |
Papua New Guinea: Circa 256 interviews (25% of the sample) last up to 11:53 minutes. The minimum LOI is 4:00 minutes.
Fiji: Circa 257 (25% of the sample) interviews last up to 11:24 minutes. The minimum LOI is 3:48 minutes.
Solomon Islands: Circa 132 (25% of the sample) interviews last up to 17:35 minutes. The minimum LOI is 07:41 minutes.
New Caledonia: Circa 128 (25% of the sample) interviews last up to 07:23 minutes. The minimum LOI is 05:00 minutes.
Vanuatu: Circa 129 (25% of the sample) interviews last up to 13:03 minutes. The minimum LOI is 05:12 minutes.
French Polynesia: Circa 128 (25% of the sample) interviews last up to 08:32 minutes. The minimum LOI is 04:42 minutes.
Samoa: Circa 129 (25% of the sample) interviews last up to 08:53 minutes. The minimum LOI is 05:01 minutes.
Tonga: Circa 126 (25% of the sample) interviews last up to 08:10 minutes. The minimum LOI is 04:59 minutes.
Cook Islands: Circa (25% of the sample) 70 interviews last up to 08:33 minutes. The minimum LOI is 04:40 minutes.
Tuvalu: Circa 40 interviews (25% of the sample) last up to 09:50 minutes. The minimum LOI is 05:31 minutes.
Niue: Circa 20 interviews (25% of the sample) last up to 12:40 minutes. The minimum LOI is 07:09 minutes.
Tokelau: Circa 15 interviews (25% of the sample) last up to 07:01 minutes. The minimum LOI is 05:09 minutes.
Federated States of Micronesia: Circa 127 interviews (25% of the sample) last up to 06:10 minutes. The minimum LOI is 04:56 minutes.
Kiribati: Circa 126 interviews (25% of the sample) last up to 06:48 minutes. The minimum LOI is 04:47 minutes.
Marshall Islands: Circa 65 interviews (25% of the sample) last up to 08:15 minutes. The minimum LOI is 04:28 minutes.
Palau: Circa 64 interviews (25% of the sample) last up to 07:17 minutes. The minimum LOI is 04:28 minutes.
Nauru: Circa 25 interviews (25% of the sample) last up to 08:45 minutes. The minimum LOI is 05:32 minutes.
5.Interview’s time of the day.
The interview’s time of the day helps to understand what type of respondents were collected. It is expected that the profile of respondents who are available to answer surveys during working hours will be different from those who are available to answer surveys outside of working hours. To avoid respondent bias due to the time of day when one communicates with the respondent, it is important to cover a broad spectrum of the time of day when interviews are conducted, including all possible population profiles.
In addition, this review helps to understand the interviewers’ work and account for whether the surveys were conducted at atypical times such as late at night or in the morning hours. A high number of cases in these atypical hours could indicate manipulation of the data by the interviewers.
The table below shows the number of cases surveyed by the time of day and country. In general, interviews were conducted during working hours and, to a lesser extent, outside working hours. There is only a low concentration of atypical cases collected late at night in Kiribati (38). While many markets have some cases at atypical times, the greatest concentration of interviews is conducted between 9 am and 6 pm.
| COUNTRY | Moment_day | Count |
|---|---|---|
| PNG | Afternoon(Between 12 and 18) | 599 |
| PNG | Early moorning (Between 6 and 9 am) | 6 |
| PNG | Morning (Between 9 and 12) | 420 |
| Fiji | Afternoon(Between 12 and 18) | 514 |
| Fiji | Evening(Between 18 and 21) | 159 |
| Fiji | Morning (Between 9 and 12) | 356 |
| Solomon Islands | Afternoon(Between 12 and 18) | 356 |
| Solomon Islands | Morning (Between 9 and 12) | 173 |
| New Caledonia | Afternoon(Between 12 and 18) | 290 |
| New Caledonia | Early moorning (Between 6 and 9 am) | 20 |
| New Caledonia | Evening(Between 18 and 21) | 56 |
| New Caledonia | Morning (Between 9 and 12) | 137 |
| Vanuatu | Afternoon(Between 12 and 18) | 267 |
| Vanuatu | Early moorning (Between 6 and 9 am) | 22 |
| Vanuatu | Evening(Between 18 and 21) | 93 |
| Vanuatu | Morning (Between 9 and 12) | 134 |
| French Polynesia | Afternoon(Between 12 and 18) | 291 |
| French Polynesia | Early moorning (Between 6 and 9 am) | 17 |
| French Polynesia | Evening(Between 18 and 21) | 86 |
| French Polynesia | Late night(Between 21 and 24) | 9 |
| French Polynesia | Morning (Between 9 and 12) | 108 |
| Samoa | Afternoon(Between 12 and 18) | 254 |
| Samoa | Early moorning (Between 6 and 9 am) | 9 |
| Samoa | Evening(Between 18 and 21) | 97 |
| Samoa | Late night(Between 21 and 24) | 38 |
| Samoa | Morning (Between 9 and 12) | 117 |
| Tonga | Afternoon(Between 12 and 18) | 305 |
| Tonga | Early moorning (Between 6 and 9 am) | 8 |
| Tonga | Evening(Between 18 and 21) | 51 |
| Tonga | Late night(Between 21 and 24) | 10 |
| Tonga | Morning (Between 9 and 12) | 130 |
| Cook Islands | Afternoon(Between 12 and 18) | 144 |
| Cook Islands | Early moorning (Between 6 and 9 am) | 6 |
| Cook Islands | Evening(Between 18 and 21) | 71 |
| Cook Islands | Late night(Between 21 and 24) | 6 |
| Cook Islands | Morning (Between 9 and 12) | 52 |
| Tuvalu | Afternoon(Between 12 and 18) | 83 |
| Tuvalu | Early moorning (Between 6 and 9 am) | 3 |
| Tuvalu | Evening(Between 18 and 21) | 32 |
| Tuvalu | Morning (Between 9 and 12) | 42 |
| Niue | Afternoon(Between 12 and 18) | 34 |
| Niue | Early moorning (Between 6 and 9 am) | 3 |
| Niue | Evening(Between 18 and 21) | 19 |
| Niue | Late night(Between 21 and 24) | 4 |
| Niue | Morning (Between 9 and 12) | 18 |
| Tokelau | Afternoon(Between 12 and 18) | 46 |
| Tokelau | Early moorning (Between 6 and 9 am) | 1 |
| Tokelau | Evening(Between 18 and 21) | 5 |
| Tokelau | Morning (Between 9 and 12) | 6 |
| FSM | Afternoon(Between 12 and 18) | 251 |
| FSM | Early moorning (Between 6 and 9 am) | 18 |
| FSM | Evening(Between 18 and 21) | 109 |
| FSM | Late night(Between 21 and 24) | 9 |
| FSM | Morning (Between 9 and 12) | 120 |
| Kiribati | Afternoon(Between 12 and 18) | 259 |
| Kiribati | Early moorning (Between 6 and 9 am) | 12 |
| Kiribati | Evening(Between 18 and 21) | 104 |
| Kiribati | Late night(Between 21 and 24) | 18 |
| Kiribati | Morning (Between 9 and 12) | 112 |
| Marshall Islands | Afternoon(Between 12 and 18) | 139 |
| Marshall Islands | Evening(Between 18 and 21) | 59 |
| Marshall Islands | Late night(Between 21 and 24) | 8 |
| Marshall Islands | Morning (Between 9 and 12) | 55 |
| Palau | Afternoon(Between 12 and 18) | 147 |
| Palau | Early moorning (Between 6 and 9 am) | 9 |
| Palau | Evening(Between 18 and 21) | 23 |
| Palau | Late night(Between 21 and 24) | 4 |
| Palau | Morning (Between 9 and 12) | 72 |
| Nauru | Afternoon(Between 12 and 18) | 59 |
| Nauru | Early moorning (Between 6 and 9 am) | 1 |
| Nauru | Evening(Between 18 and 21) | 20 |
| Nauru | Late night(Between 21 and 24) | 1 |
| Nauru | Morning (Between 9 and 12) | 20 |