rm(list=ls(all=t))

Setup filenames

filename <- "ecsection4_relabelled" # !!!Update filename
functions_vers <-  "functions_1.7.R" # !!!Update helper functions file

Setup data, functions and create dictionary for dataset review

source (functions_vers)
## --------
## This is sdcMicro v5.6.0.
## For references, please have a look at citation('sdcMicro')
## Note: since version 5.0.0, the graphical user-interface is a shiny-app that can be started with sdcApp().
## Please submit suggestions and bugs at: https://github.com/sdcTools/sdcMicro/issues
## --------
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
## Loading required package: sp
## Checking rgeos availability: TRUE
## 
## Attaching package: 'raster'
## The following object is masked from 'package:dplyr':
## 
##     select
## The following object is masked from 'package:sdcMicro':
## 
##     freq
## rgdal: version: 1.5-23, (SVN revision 1121)
## Geospatial Data Abstraction Library extensions to R successfully loaded
## Loaded GDAL runtime: GDAL 3.2.1, released 2020/12/29
## Path to GDAL shared files: C:/Users/Usuario/Documents/R/win-library/3.6/rgdal/gdal
## GDAL binary built with GEOS: TRUE 
## Loaded PROJ runtime: Rel. 7.2.1, January 1st, 2021, [PJ_VERSION: 721]
## Path to PROJ shared files: C:/Users/Usuario/Documents/R/win-library/3.6/rgdal/proj
## PROJ CDN enabled: FALSE
## Linking to sp version:1.4-5
## To mute warnings of possible GDAL/OSR exportToProj4() degradation,
## use options("rgdal_show_exportToProj4_warnings"="none") before loading rgdal.
## Overwritten PROJ_LIB was C:/Users/Usuario/Documents/R/win-library/3.6/rgdal/proj
## Loading required package: spatstat.data
## Loading required package: spatstat.geom
## spatstat.geom 2.1-0
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## Attaching package: 'spatstat.geom'
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##     area, rotate, shift
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## Attaching package: 'nlme'
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## spatstat.core 2.1-2
## Loading required package: spatstat.linnet
## spatstat.linnet 2.1-1
## 
## spatstat 2.1-0       (nickname: 'Comedic violence') 
## For an introduction to spatstat, type 'beginner'
## rgeos version: 0.5-5, (SVN revision 640)
##  GEOS runtime version: 3.8.0-CAPI-1.13.1 
##  Linking to sp version: 1.4-5 
##  Polygon checking: TRUE
## 
## Spatial Point Pattern Analysis Code in S-Plus
##  
##  Version 2 - Spatial and Space-Time analysis
## 
## Attaching package: 'splancs'
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##     zoom
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## Loading required package: spam
## Loading required package: dotCall64
## Loading required package: grid
## Spam version 2.6-0 (2020-12-14) is loaded.
## Type 'help( Spam)' or 'demo( spam)' for a short introduction 
## and overview of this package.
## Help for individual functions is also obtained by adding the
## suffix '.spam' to the function name, e.g. 'help( chol.spam)'.
## 
## Attaching package: 'spam'
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##     backsolve, forwardsolve
## See https://github.com/NCAR/Fields for
##  an extensive vignette, other supplements and source code
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Visually inspect variables in "dictionary.csv" and flag for risk, using the following flags:

# Direct PII: Respondent Names, Addresses, Identification Numbers, Phone Numbers
# Direct PII-team: Interviewer Names, other field team names 
# Indirect PII-ordinal: Date of birth, Age, income, education, household composition. 
# Indirect PII-categorical: Gender, education, ethnicity, nationality,
# occupation, employer, head of household, marital status
# GPS: Longitude, Latitude
# Small Location: Location (<100,000) 
# Large Location (>100,000)
# Weight: weightVar
# Household ID:  hhId, 
# Open-ends: Review responses for any sensitive information, redact as necessary 

Direct PII: variables to be removed

# !!! No Direct PII

Direct PII-team: Encode field team names

!!! No Direct PII-team

Small locations: Encode locations with pop <100,000 using random large numbers

dropvars <- c("dise") 
mydata <- mydata[!names(mydata) %in% dropvars]

locvars <- c("q002_blckid", "q003_vill_id") 
mydata <- encode_location (variables= locvars, missing=999999)
## [1] "Frequency table before encoding"
## q002_blckid. 002 Unique block ID
##   1   2   3   4   5   6   7   8   9 
## 206 167 188 412  96 192 158 424 544 
## [1] "Frequency table after encoding"
## q002_blckid. 002 Unique block ID
## 279 280 281 282 283 284 285 286 287 
## 206 544 167 424  96 188 412 158 192 
## [1] "Frequency table before encoding"
## q003_vill_id. 003 Village ID
##    1    2    3    4    5    6    7    8    9   10   11   12   13   15   16   17   18 
##   17   16   17   16   20   29   29   16   15   13   17   26   24   14   18   21   18 
##   19   20   21   22   23   24   25   26   27   28   29   30   31   32   33   34   35 
##   18   20   30   23   18   18   32   25   27   17   14   13   24   26   21   16   28 
##   36   37   38   39   40   41   42   43   44   45   46   47   48   49   50   51   52 
##   19   15   22   27   16   16   18   16   27   21   22   21   20   17   17   17   18 
##   53   54   55   56   57   58   59   60   61   62   63   64   65   66   67   68   69 
##   27   25   27   19   13   21   12   24   19   17   19   18   30   16   19   21   25 
##   70   71   72   73   74   75   76   77   78   80   81   82   83   84   85   87   88 
##   13   16   21   16   23   22   18   23   30   30   16   21   17   17   13   18   22 
##   89   90   91   92   93   94   95   96   97   98   99  100  101  102  103  104  105 
##   16   19   20   18   20   14   20   24   28   21   26   17   25   20   15   19   16 
##  106  107  108  109  110  111  112  113  114  115  116  117  118  119  120  121  122 
##   31   13   28   22   17   21   27   15   24   20   14   24   22   21   13   13   10 
## <NA> 
##    1 
## [1] "Frequency table after encoding"
## q003_vill_id. 003 Village ID
##  609  610  611  612  613  614  615  616  617  618  619  620  621  622  623  624  625 
##   18   16   24   20   21   16   27   13   20   18   19   17   23   17   10   21   19 
##  626  627  628  629  630  631  632  633  634  635  636  637  638  639  640  641  642 
##   18   24   24   16   27   23   32   21   28   19   16   16   30   25   21   20   27 
##  643  644  645  646  647  648  649  650  651  652  653  654  655  656  657  658  659 
##   21   28   18   29   25   25   16   17   20   24   17   31   15   21   17   13   26 
##  660  661  662  663  664  665  666  667  668  669  670  671  672  673  674  675  676 
##   26   22   30   12   14   18   27   14   15   17   23   21   24   22   22   20   21 
##  677  678  679  680  681  682  683  684  685  686  687  688  689  690  691  692  693 
##   21   27   17   16   30   13   24   19   20   18   17   16   16   29   16   21   22 
##  694  695  696  697  698  699  700  701  702  703  704  705  706  707  708  709  710 
##   18   16   14   16   19   18   17   28   19   25   13   13   21   13   17   15   20 
##  711  712  713  714  715  716  717  718  719  720  721  722  723  724  725  726  727 
##   22   27   30   22   16   13   14   20   26   17   19   18   18   15   18   17   13 
## <NA> 
##    1

Indirect PII - Ordinal: Global recode or Top/bottom coding for extreme values

!!! No action as variables are critical for analysis #Indirect PII - Categorical: Recode, encode, or Top/bottom coding for extreme values

indirect_PII <- c("q401_wrkdne_bfresunrise",
                  "q402_prob_inadqlight",
                  "q403_loudnoise_wrk",
                  "q404_wrk_extrmtemp",
                  "q405_wrk_brickcement",
                  "q406_wrk_stonebk_crush",
                  "q407_polish_gntestone",
                  "q408_wrk_construction",
                  "q409_wrk_carryhvy_load",
                  "q410_wrk_opertmachine",
                  "q411_wrk_injured",
                  "q412_wrk_hndlchemicls",
                  "q413_wrk_werglovmsk",
                  "q414_health_inwrk",
                  "q415_wrk_danger",
                  "q416_wrk_whodecids",
                  "q417_descrb_wrksite",
                  "q418_wrk_wrksite_lst12m",
                  "q419_dayoff_ifnotwell",
                  "q420_refdngtask_atwrk",
                  "q421_leavwrk_ifwanted",
                  "q422a_wrkng_offdebt",
                  "q422b_parent_punish",
                  "q422c_emplr_punish",
                  "q422d_noothwrk_avble",
                  "q422e_notengh_mny",
                  "q422f_dk_whrtogo",
                  "q422g_resp_eldrdecisn",
                  "q422h_fear_parents",
                  "q422i_parent_illness",
                  "q422j_finshrtg_hh",
                  "q422k_helpmthr",
                  "q422l_bczmthr_wrks",
                  "q422m_lovefor_wrk",
                  "q422n_noone_wrkathome",
                  "q422o_eldsib_athome",
                  "q422p_noone_infmly_gvemny",
                  "q422q_dkntwnt_leav",
                  "q422r_noone_athome",
                  "q422s_toern_mnysupp_edu",
                  "q422t_erntofeed_cattle",
                  "q422u_assist_sis",
                  "q422v_others",
                  "q423_hrswrk_lst12m",
                  "q424a_cash",
                  "q424b_newskill",
                  "q424c_education",
                  "q424d_shelter_foodcloths",
                  "q424e_medicalsupp",
                  "q424f_nothing",
                  "q424g_toys",
                  "q424h_fruits_veg",
                  "q424i_chocolate",
                  "q424j_dryfruit",
                  "q424k_bangles",
                  "q424l_jewellery",
                  "q424m_breakfast",
                  "q424n_utensils",
                  "q424o_snacks",
                  "q425_emplr_ben_parent",
                  "q426_earn_inaweek")

capture_tables (indirect_PII)

!!! No action as variables are critical for analysis #Open-ends: review responses for any sensitive information, redact as necessary !!! No open-ends

# Drop all, as actually verbatim data in Hindi
mydata <- mydata[!names(mydata) %in% "q416_whether_oth"]
mydata <- mydata[!names(mydata) %in% "q417_desc_site_oth"]

GPS data: Displace

!!! No GPS data

Save processed data in Stata and SPSS format

haven::write_dta(mydata, paste0(filename, "_PU.dta"))
haven::write_sav(mydata, paste0(filename, "_PU.sav"))

# Add report title dynamically
title_var <- paste0("DOL-ILAB SDC - ", filename)