Debug sa design

[sou412]

Debug functions related to the SA design

• Address an issue that estimates become NA when there are not sufficiently long post-treatment periods
• Address an issue in plot() function that produce an error when the treatment variable is named other than treatment

##
## Sances example 
##

require(DIDdesign)
#> Loading required package: DIDdesign
require(dplyr)
#> Loading required package: dplyr
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
data(sances2015)

## prepare data 
data_use <- sances2015 %>%
  mutate(id_time = year, id_subject = as.numeric(as.factor(swis_code)))

## remove observations that are treated at early time points
Dmean <- data_use %>% group_by(id_subject) %>% summarise(across(treatment, mean))
#> `summarise()` ungrouping output (override with `.groups` argument)
data_use2 <- data_use %>% 
  filter(!(id_subject %in% Dmean$id_subject[Dmean$treatment > 0.85])) %>% 
  mutate(id_subject = as.numeric(as.factor(as.character(id_subject))))

## example 
set.seed(1234)
fit_sa_dyn <- did(
  formula = reassessed ~ treatment,
  data    = data_use2,
  id_unit = "id_subject",
  id_time = "id_time",
  design  = "sa",
  option  = list(n_boot = 10, parallel = TRUE, lead = 0:5, thres = 1)
)

summary(fit_sa_dyn)
#> ── ATT Estimates ───────────────────────────────────────────────────────────────
#>        estimator lead estimate std.error statistic p_value
#> 1  SA-Double-DID    0   -1.672       9.2    -0.182 0.85580
#> 2         SA-DID    0    1.691       2.6     0.642 0.52064
#> 3        SA-sDID    0   -0.401       5.6    -0.071 0.94328
#> 4  SA-Double-DID    1   -5.110      11.0    -0.466 0.64126
#> 5         SA-DID    1    2.584       3.5     0.743 0.45762
#> 6        SA-sDID    1   -1.200       5.1    -0.235 0.81383
#> 7  SA-Double-DID    2    4.529       5.3     0.859 0.39032
#> 8         SA-DID    2    9.135       3.5     2.610 0.00906
#> 9        SA-sDID    2    4.682       5.1     0.919 0.35810
#> 10 SA-Double-DID    3   -6.555       8.9    -0.735 0.46228
#> 11        SA-DID    3   10.648       3.2     3.338 0.00084
#> 12       SA-sDID    3    0.071       5.3     0.013 0.98945
#> 13 SA-Double-DID    4   -3.202       6.1    -0.526 0.59867
#> 14        SA-DID    4   10.236       4.5     2.255 0.02412
#> 15       SA-sDID    4   -2.360       5.7    -0.414 0.67859
#> 16 SA-Double-DID    5    1.834       4.1     0.446 0.65553
#> 17        SA-DID    5    9.219       4.1     2.250 0.02447
#> 18       SA-sDID    5    0.402       4.8     0.083 0.93387

plot(fit_sa_dyn)

^{Created on 2021-04-08 by the reprex package (v0.3.0)}