grab_predictors: grab_predictors

In tidysynth: A Tidy Implementation of the Synthetic Control Method

grab_predictors

Description

Extract the aggregate-level covariates generated by generate_predictor() from the synth pipeline.

Usage

grab_predictors(data, type = "treated", placebo = FALSE)

Arguments

data	nested data of type tbl_df
type	string specifying which version of the data to extract: "treated" or "control". Default is "treated".
placebo	boolean flag; if TRUE placebo values are returned as well (if available). Default is FALSE.

Value

tibble data frame

Examples

# Smoking example data
data(smoking)

smoking_out <-
smoking %>%

# initial the synthetic control object
synthetic_control(outcome = cigsale,
                  unit = state,
                  time = year,
                  i_unit = "California",
                  i_time = 1988,
                  generate_placebos=FALSE) %>%

# Generate the aggregate predictors used to generate the weights
  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 the fitted weights for the synthetic control
  generate_weights(optimization_window =1970:1988,
                   Margin.ipop=.02,Sigf.ipop=7,Bound.ipop=6) %>%

  # Generate the synthetic control
  generate_control()

# Grab predictors data frame for the treated unit
smoking_out %>% grab_predictors()

# Grab predictors data frame for control units
smoking_out %>% grab_predictors(type="controls")

tidysynth documentation built on May 31, 2023, 6:13 p.m.