eiCompare (version 3.0.0)

ei_rc_good_table: Create EI Comparison Table

Description

Takes output from EI model, EI RxC model, Goodman regression, and puts them into a data frame table for useful analysis and comparison.

Usage

ei_rc_good_table(ei, rc, good, groups, include_good = FALSE)

Arguments

ei

Table/data frame object result from ei_est_gen. This assumes beta_yes=FALSE in ei_est_gen(). See example below for beta_yes=TRUE in ei_est_gen().

rc

Table/data frame from EI:RxC process from bayes_table_make()

good

Table/data frame from Goodman regression, from goodman_generalize(). Default is nothing

groups

Character vector of voting blocks (e.g., c("Latino", "White"))

include_good

Logical, default is FALSE, Set to TRUE if including a Goodman table/data object

Value

Object of class ei_compare containing a 1. data.frame() slot of comparisons across the three models; 2. Character vector of group names used for later plotting

References

eiPack, King et. al. (http://gking.harvard.edu/eiR)

Examples

# NOT RUN {
# }
# NOT RUN {
# TOY DATA EXAMPLE
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!
results <- ei_est_gen(cands, race_group, "total",
  data = toy[c(1, 3, 5), ], table_names = table_names, sample = 100
)

# Generate formula for passage to ei.reg.bayes() function
form <- formula(cbind(canda, candb) ~ cbind(black, white))
# Run Bayesian model
suppressWarnings(
  ei_bayes <- ei.reg.bayes(form, data = toy, sample = 100, truncate = TRUE)
)

table_names <- c("RxC: PCT Black", "RxC: PCT White")
cands <- c("canda", "candb")
ei_bayes_res <- bayes_table_make(ei_bayes,
  cand_vector = cands,
  table_names = table_names
)
ei_bayes_res <- ei_bayes_res[c(1, 2, 5), ]
# Combine Results, results in object of class ei_compare
ei_rc_combine <- ei_rc_good_table(results, ei_bayes_res,
  groups = c("Black", "White")
)
# Produces data and character vector, which can be sent to plot()
ei_rc_combine

# Warning: Takes a while to run
# Load corona data
data(corona)
# Generate 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 Lat", "EI: Pct Asian", "EI: Pct White")
# Run EI iterative Fitting
results <- ei_est_gen(
  cand_vector = cands,
  race_group = race_group3,
  total = "totvote",
  data = corona,
  table_names = table_names
)

# EI: RxC model
# Generate formula
form <- formula(cbind(
  pct_husted,
  pct_spiegel,
  pct_ruth,
  pct_button,
  pct_montanez,
  pct_fox
) ~ cbind(pct_hisp, pct_asian, pct_white))
suppressWarnings(
  ei_bayes <- ei.reg.bayes(form,
    data = corona,
    sample = 10000,
    truncate = TRUE
  )
)
# RxC table names
table_names <- c("RxC: Pct Hisp", "RxC: Pct Asian", "RxC: Pct White")
# Table Creation, using function bayes_table_make in ei_est_generalize.R file
ei_bayes_res <- bayes_table_make(ei_bayes,
  cand_vector = cands,
  table_names = table_names
)


# Combine Results, results in object of class ei_compare
ei_rc_combine <- ei_rc_good_table(results,
  ei_bayes_res,
  groups = c("Latino", "Asian", "White")
)
ei_rc_combine

# If set beta_yes = TRUE in ei_est_gen():
ei_rc_combine2 <- ei_rc_good_table(results[[1]],
  ei_bayes_res,
  groups = c("Black", "White")
)
# }
# NOT RUN {
# }