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This function adds dummy variables to an individual-level dataframe for all school-aged children. It creates a variable (edu_ind_access_d) that indicates whether the child accessed school (1 if accessed, 0 if explicitly not accessed) and another variable (edu_ind_no_access_d) that indicates no access to school.

Prerequisite function:

  • add_loop_edu_ind_age_corrected.R

Usage

add_loop_edu_access_d(
  loop,
  ind_access = "edu_access",
  yes = "yes",
  no = "no",
  pnta = "pnta",
  dnk = "dnk",
  ind_schooling_age_d = "edu_ind_age_schooling"
)

add_loop_edu_access_d_to_main(
  main,
  loop,
  ind_access_d = "edu_ind_access_d",
  ind_no_access_d = "edu_ind_no_access_d",
  id_col_main = "uuid",
  id_col_loop = "uuid"
)

Arguments

loop

A data frame of individual-level data for the loop.

ind_access

Column name for education access.

yes

Value indicating access to education (e.g., "yes").

no

Value indicating no access to education (e.g., "no").

pnta

Value indicating prefer not to answer (e.g., "pnta").

dnk

Value indicating don't know (e.g., "dnk").

ind_schooling_age_d

Column name for the dummy variable indicating schooling age.

main

A data frame of household-level data.

ind_access_d

Column name for education access (binary).

ind_no_access_d

Column name for education no access (binary).

id_col_main

Column name for the unique identifier in the main dataset.

id_col_loop

Column name for the unique identifier in the loop dataset.

Value

A data frame with additional columns:

  • edu_ind_access_d: Dummy variable indicating access to education (1 if accessed, 0 if explicitly not accessed, NA if not school age or pnta/dnk).

  • edu_ind_no_access_d: Dummy variable indicating no access to education (1 if explicitly not accessed, 0 if accessed, NA if not school age or pnta/dnk).

Details

pnta (prefer not to answer) and dnk (don't know) responses are coded as NA, not as "not accessed"