Significance testing of differences with MOEs

Source: R/moe_test.R

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.

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)
#>        name men_est men_moe women_est women_moe diff       se1       se2
#> 1    Hamden    37.2     1.9      37.8       1.9  0.6 1.1551180 1.1551180
#> 2 New Haven    29.5     0.8      31.9       0.8  2.4 0.4863655 0.4863655
#>          se   z_score isSig_10
#> 1 1.6335835 0.3672907     TRUE
#> 2 0.6878246 3.4892615     TRUE