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
)
A data frame
Estimate for first group
Margin of error for first group
Estimate for second group
Margin of error for second group
Confidence level used in calculating MOEs given; defaults to 0.9, per ACS data
Alpha used for significance testing; defaults to 0.05
Logical, whether to keep intermediary calculations (default) or only result of testing
A tibble/data frame with testing-related columns added
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