Group-by-time outcome means for parallel-trends visualisation

Usage

morie_did_parallel_trends_data(data, outcome, treatment, time, weights = NULL)

Arguments

data: A data frame.
outcome, treatment, time: Column names.
weights: Optional survey weight column.

Value

A data frame with columns time, group, mean_outcome, se, n.

Examples

set.seed(1)
df <- expand.grid(unit = 1:30, time = 1:6)
df$treat <- as.integer(df$unit <= 15)
df$d <- as.integer(df$treat == 1L & df$time >= 4)
df$y <- 0.1 * df$time + 0.7 * df$d + rnorm(nrow(df), sd = 0.4)
out <- morie_did_parallel_trends_data(df, "y", "treat", "time")
head(out)
#>   time group mean_outcome         se  n
#> 1    1     0    0.1256294 0.08839741 15
#> 2    2     0    0.2701053 0.09163341 15
#> 3    3     0    0.3162049 0.07067181 15
#> 4    4     0    0.5136613 0.08718649 15
#> 5    5     0    0.2698651 0.11293979 15
#> 6    6     0    0.8163415 0.10952473 15