df_pcdv is a helper function to perform prediction-correction
of observed or simulated depedent variables.
Usage
df_pcdv(
data,
bin_var = "NTIME",
strat_vars = NULL,
dvpred_vars = c(PRED = "PRED", DV = "DV"),
lower_bound = 0
)Arguments
- data
Input dataset
- bin_var
Exact binning variable. Default is
"NTIME".- strat_vars
Stratifying variables. Default is
NULL.- dvpred_vars
Names of variables for the dependent variable and population model prediction. Must be named character vector. Defaults are
"PRED"and"DV".- lower_bound
Lower bound of the dependent variable for prediction correction. Default is
0.
Value
A data.frame containing one row per unique combination of
bin_var and strat_vars and new variable PCDV containing
prediction-corrected observations.
Examples
model <- model_mread_load(model = "model")
#> Loading model from cache.
data <- df_addpred(data_sad, model)
simout <- df_pcdv(data, dvpred_vars = c(DV = "ODV", PRED = "PRED"))