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Calculate equity access rate

Source: R/percentile_rank.R
calculate_access_rate.Rd

Calculates the share of students (overall or by subgroup) attending schools that meet or exceed a performance threshold. This replicates the MarGrady metric: "the share of Black students in Newark attending a school that beat the state proficiency average."

Usage

calculate_access_rate(
  df_enrollment,
  df_performance,
  performance_metric = "proficient_above",
  threshold_type = c("state_avg", "absolute", "percentile"),
  threshold_value = NULL,
  enrollment_col = "n_students",
  subgroup = NULL,
  join_cols = c("end_year", "county_id", "district_id", "school_id")
)

Arguments

df_enrollment

School-level enrollment data with demographic counts

df_performance

School-level performance data

performance_metric

Character. Column in df_performance to use as the performance measure. Default "proficient_above".

threshold_type

Character. How to define "high-performing":

  • "state_avg": Above the state average for that year/grade/subject

  • "absolute": Above a fixed numeric threshold

  • "percentile": Above a percentile threshold within peers

threshold_value

Numeric. The threshold value. Required for "absolute" and "percentile" types. For "state_avg", this is ignored.

enrollment_col

Character. Column in df_enrollment containing student counts. Default "n_students".

subgroup

Character. Which subgroup to calculate access for. If NULL, calculates for total enrollment. Default NULL.

join_cols

Character vector. Columns to join enrollment and performance data on. Default c("end_year", "county_id", "district_id", "school_id").

Value

Dataframe with columns:

  • Year and entity identifiers

  • n_students_total: Total students in subgroup

  • n_students_above: Students in above-threshold schools

  • pct_access: Percent with access to high-performing schools