Add Physical Water Access Issue Indicator
Source:R/add_water_access_issue.R
add_water_access_issue_physical.RdComputes a binary variable (wash_water_access_issue_physical_infrastructure_d) that is 1L if the household reported any physical or infrastructure-related barrier to accessing water points (too far, difficult to use, disability-related barriers, safety concerns, excessive waiting time, not segregated by gender, some groups lacking access, an out-of-service source, intermittent/infrequent service, closed water points, or not enough containers), 0L if none were reported, and NA if the response was ambiguous (dnk/pnta/other) or any component is missing.
Computes a binary variable (wash_water_access_issue_financial_market_d) that is 1L if the household reported any financial or market-related barrier to accessing water (water not available at the market, or too expensive), 0L if none were reported, and NA if the response was ambiguous (dnk/pnta/other) or any component is missing.
Usage
add_water_access_issue_physical(
df,
water_access_issue = "wash_water_access_issue",
physical = c("waterpoints_too_far", "waterpoints_difficult_use",
"disability_no_access_waterpoints", "safety_concerns_waterpoints",
"safety_concerns_travel_waterpoints", "excessive_waiting_time_waterpoints",
"water_source_not_segregated_gender", "groups_no_access_waterpoints",
"water_source_not_functional", "intermittent_infrequent_service",
"waterpoints_not_functioning_closed", "not_enough_containers"),
undefined = c("dnk", "pnta", "other"),
sep = "/"
)
add_water_access_issue_financial(
df,
water_access_issue = "wash_water_access_issue",
financial = c("water_not_available_market", "water_too_expensive"),
undefined = c("dnk", "pnta", "other"),
sep = "/"
)Arguments
- df
A data frame.
- water_access_issue
Base name of the select_multiple variable.
- physical
Character vector of responses that indicate physical or infrastructure-related access barriers.
- undefined
Character vector of undefined responses (dnk, pnta, other).
- sep
Separator between the base name and response code in binary column names.
- financial
Character vector of responses that indicate financial or market-related access barriers.
Value
A data frame with one additional column:
wash_water_access_issue_physical_infrastructure_d:1Lif any physical or infrastructure-related barrier is reported;0Lif none;NAif the response is undefined or any component is missing.
A data frame with one additional column:
wash_water_access_issue_financial_market_d:1Lif any financial or market-related barrier is reported;0Lif none;NAif the response is undefined or any component is missing.
Examples
df <- data.frame(
wash_water_access_issue = c(
"waterpoints_too_far", "no_problem_access_water", "dnk"
),
`wash_water_access_issue/waterpoints_too_far` = c(1L, 0L, 0L),
`wash_water_access_issue/waterpoints_difficult_use` = c(0L, 0L, 0L),
`wash_water_access_issue/disability_no_access_waterpoints` = c(0L, 0L, 0L),
`wash_water_access_issue/safety_concerns_waterpoints` = c(0L, 0L, 0L),
`wash_water_access_issue/safety_concerns_travel_waterpoints` = c(0L, 0L, 0L),
`wash_water_access_issue/excessive_waiting_time_waterpoints` = c(0L, 0L, 0L),
`wash_water_access_issue/water_source_not_segregated_gender` = c(0L, 0L, 0L),
`wash_water_access_issue/groups_no_access_waterpoints` = c(0L, 0L, 0L),
`wash_water_access_issue/water_source_not_functional` = c(0L, 0L, 0L),
`wash_water_access_issue/intermittent_infrequent_service` = c(0L, 0L, 0L),
`wash_water_access_issue/waterpoints_not_functioning_closed` = c(0L, 0L, 0L),
`wash_water_access_issue/not_enough_containers` = c(0L, 0L, 0L),
`wash_water_access_issue/dnk` = c(0L, 0L, 1L),
`wash_water_access_issue/pnta` = c(0L, 0L, 0L),
`wash_water_access_issue/other` = c(0L, 0L, 0L),
check.names = FALSE
)
add_water_access_issue_physical(df)
#> wash_water_access_issue wash_water_access_issue/waterpoints_too_far
#> 1 waterpoints_too_far 1
#> 2 no_problem_access_water 0
#> 3 dnk 0
#> wash_water_access_issue/waterpoints_difficult_use
#> 1 0
#> 2 0
#> 3 0
#> wash_water_access_issue/disability_no_access_waterpoints
#> 1 0
#> 2 0
#> 3 0
#> wash_water_access_issue/safety_concerns_waterpoints
#> 1 0
#> 2 0
#> 3 0
#> wash_water_access_issue/safety_concerns_travel_waterpoints
#> 1 0
#> 2 0
#> 3 0
#> wash_water_access_issue/excessive_waiting_time_waterpoints
#> 1 0
#> 2 0
#> 3 0
#> wash_water_access_issue/water_source_not_segregated_gender
#> 1 0
#> 2 0
#> 3 0
#> wash_water_access_issue/groups_no_access_waterpoints
#> 1 0
#> 2 0
#> 3 0
#> wash_water_access_issue/water_source_not_functional
#> 1 0
#> 2 0
#> 3 0
#> wash_water_access_issue/intermittent_infrequent_service
#> 1 0
#> 2 0
#> 3 0
#> wash_water_access_issue/waterpoints_not_functioning_closed
#> 1 0
#> 2 0
#> 3 0
#> wash_water_access_issue/not_enough_containers wash_water_access_issue/dnk
#> 1 0 0
#> 2 0 0
#> 3 0 1
#> wash_water_access_issue/pnta wash_water_access_issue/other
#> 1 0 0
#> 2 0 0
#> 3 0 0
#> wash_water_access_issue_physical_infrastructure_d
#> 1 1
#> 2 0
#> 3 NA
df <- data.frame(
wash_water_access_issue = c(
"water_too_expensive", "no_problem_access_water", "dnk"
),
`wash_water_access_issue/water_not_available_market` = c(0L, 0L, 0L),
`wash_water_access_issue/water_too_expensive` = c(1L, 0L, 0L),
`wash_water_access_issue/dnk` = c(0L, 0L, 1L),
`wash_water_access_issue/pnta` = c(0L, 0L, 0L),
`wash_water_access_issue/other` = c(0L, 0L, 0L),
check.names = FALSE
)
add_water_access_issue_financial(df)
#> wash_water_access_issue wash_water_access_issue/water_not_available_market
#> 1 water_too_expensive 0
#> 2 no_problem_access_water 0
#> 3 dnk 0
#> wash_water_access_issue/water_too_expensive wash_water_access_issue/dnk
#> 1 1 0
#> 2 0 0
#> 3 0 1
#> wash_water_access_issue/pnta wash_water_access_issue/other
#> 1 0 0
#> 2 0 0
#> 3 0 0
#> wash_water_access_issue_financial_market_d
#> 1 1
#> 2 0
#> 3 NA