eiCompare (version 3.0.0)

ei_est_gen: Iterative EI Estimation

Description

Iteratively fits EI models for candidates and racial/ethnic groups

Usage

ei_est_gen(
  cand_vector,
  race_group,
  total,
  rho = 10,
  data,
  table_names,
  sample = 1000,
  tomog = F,
  density_plot = F,
  beta_yes = F,
  seed = NULL,
  ...
)

Arguments

cand_vector

Character vector of candidate names, taken from the dataset

race_group

Character vector of formula, e.g., "~ pct_latino"

total

Character vector (e.g., "totvote") of total variable name from data, variable in data is numeric

rho

Rho parameter for ei() estimate, defaults to 10, numeric

data

data.frame() object containing the data

table_names

Character vector of table names with same length as race_group. Used for formatting output. If only one racial group, must provide "Pct. Other" as second element of vector

sample

Number of samples used for EI calculation, default = 1000

tomog

Logical to display tomography plot. If true will will save pdf plot to working directory. Default is FALSE

density_plot

Logical to display density plot of betab and betaw. If true will save pdf plot to working directory. Default is FALSE

beta_yes

Logical to export betas (b, w) in list object in addition to table of results. Default is FALSE

seed

An integer seed value for replicating estimate results across runs. If NULL, a random seed is chosen. Defaulted to NULL.

…

Arguments passed onto ei() function

Value

Data frame/table object containing EI individually estimated results. If beta_yes=TRUE, two list items, first the data frame table of results, second dataframe of betas themselves.

References

eiPack. Gary King (1997). A Solution to the Ecological Inference Problem. Princeton: Princeton University Press.

Examples

# NOT RUN {
# TOY DATA EXAMPLE
# }
# NOT RUN {
canda <- c(.1, .09, .85, .9, .92)
candb <- 1 - canda
white <- c(.8, .9, .10, .08, .11)
black <- 1 - white
total <- c(30, 80, 70, 20, 29)
toy <- data.frame(canda, candb, white, black, total)

# CREATE VECTORS
cands <- c("canda")
race_group <- c("~ black") # only use one group for example
table_names <- c("EI: PCT Black", "EI: PCT White")

# RUN ei_est_gen()
# KEEP DATA TO JUST ONE ROW FOR EXAMPLE (time) ONLY!
ei_est_gen(cands, race_group, "total",
  data = toy[c(1, 3, 5), ], table_names = table_names, sample = 100
)

# WARNING -- May take a little while to execute
# Load Package Data
data(corona)
# Create Character Vectors
cands <- c("pct_husted", "pct_spiegel", "pct_ruth", "pct_button", "pct_montanez", "pct_fox")
race_group3 <- c("~ pct_hisp", "~ pct_asian", "~ pct_white")
table_names <- c("EI: Pct Hisp", "EI: Pct Asian", "EI: Pct White")

# Run ei_est_gen function
results <- ei_est_gen(
  cand_vector = cands, race_group = race_group3,
  total = "totvote", data = corona, table_names = table_names
)

results
# Run ei_est_gen function; Exporting betas into data frame
results_w_betas <- ei_est_gen(
  cand_vector = cands, race_group = race_group3,
  total = "totvote", data = corona, table_names = table_names, beta_yes = TRUE
)

res1 <- results_w_betas[[1]] # table of mean estimates
res1
res2 <- results_w_betas[[2]] # betas of estimates for each precinct
# }
# NOT RUN {
# }

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