moe_test: Significance testing of differences with MOEs

In camille-s/camiller: Lots of convenience functions

Description

This function uses 2 estimates and 2 margins of error to do significance testing. It optionally returns the input data frame with the calculations used for testing, or just the data frame with results attached.

Usage

moe_test(
  .data,
  est1,
  moe1,
  est2,
  moe2,
  cl = 0.9,
  alpha = 0.05,
  show_calc = TRUE
)

Arguments

.data	A data frame
est1	Estimate for first group
moe1	Margin of error for first group
est2	Estimate for second group
moe2	Margin of error for second group
cl	Confidence level used in calculating MOEs given; defaults to 0.9, per ACS data
alpha	Alpha used for significance testing; defaults to 0.05
show_calc	Logical, whether to keep intermediary calculations (default) or only result of testing

Value

A tibble/data frame with testing-related columns added

Examples

med_age <- data.frame(name = c("Hamden", "New Haven"),
    men_est = c(37.2, 29.5), men_moe = c(1.9, 0.8),
    women_est = c(37.8, 31.9), women_moe = c(1.9, 0.8))
med_age %>%
  moe_test(men_est, men_moe, women_est, women_moe, alpha = 0.9, show_calc = TRUE)

camille-s/camiller documentation built on Jan. 22, 2022, 6:50 a.m.