View source: R/grab-methods.R View source: R/grab-methods.R
grab_balance_table | R Documentation |
Compare the distributions of the aggregate-level predictors for the observed intervention unit, the synthetic control, and the donor pool average. Table helps user compare the the level of balance produced by the synthetic control.
grab_balance_table(data)
data |
nested data of type |
tibble data frame containing balance statistics between the observed/synthetic unit and the donor pool for each variable used to fit the synthetic control.
data(smoking)
smoking_out <-
smoking %>%
synthetic_control(outcome = cigsale,
unit = state,
time = year,
i_unit = "California",
i_time = 1988,
generate_placebos=FALSE) %>%
generate_predictor(time_window=1980:1988,
lnincome = mean(lnincome, na.rm = TRUE),
retprice = mean(retprice, na.rm = TRUE),
age15to24 = mean(age15to24, na.rm = TRUE)) %>%
generate_predictor(time_window=1984:1988,
beer = mean(beer, na.rm = TRUE)) %>%
generate_predictor(time_window=1975,
cigsale_1975 = cigsale) %>%
generate_predictor(time_window=1980,
cigsale_1980 = cigsale) %>%
generate_predictor(time_window=1988,
cigsale_1988 = cigsale) %>%
generate_weights(optimization_window =1970:1988,
Margin.ipop=.02,Sigf.ipop=7,Bound.ipop=6) %>%
generate_control()
smoking_out %>% grab_balance_table()
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