FLAME_PostgreSQL: PostgreSQL Database Implementation

In chiarui424/FLAME: A Fast Large-Scale Almost Matching Exactly Approach to Causal Inference

Description

FLAME_PostgreSQL applies the FLAME algorithm based on PostgreSQL. If your computer system does not have PostgreSQL installed, install from here. For setup of PostgreSQL server, please refer to this tutorial. User must connect to PostgreSQL server in R using the command dbConnect(dbDriver('PostgreSQL'), dbname="your_dbname", host='your_localhost', port='your_port', user='your_username', password = 'your_password')

Usage

FLAME_PostgreSQL(db, data, holdout, compute_var = FALSE,
  tradeoff = 0.1, PE_function = NULL, model = NULL,
  ridge_reg = NULL, lasso_reg = NULL)

Arguments

db	name of the database connection
data	input data
holdout	holdout training data
compute_var	variance indicator (optional, default = FALSE)
tradeoff	Match Quality tradeoff parameter (optional, default = 0.1)
PE_function	user defined function to compute predictive error (optional)
model	Linear, Ridge, or Lasso (optional)
ridge_reg	L2 regularization parameter if model = Ridge (optional)
lasso_reg	L1 regularization parameter if model = Lasso (optional)

Value

(1) list of covariates FLAME performs matching at each iteration, (2) Sizes, conditional average treatment effects (CATEs), and variance (if compute_var = TRUE) of matches at each iteration, (3) match quality at each iteration, and (4) the original data with additional column *matched*, indicating the number of covariates each unit is matched on. If a unit is never matched, then *matched* will be 0.

Examples

data <- data(toy_data)

drv <- dbDriver('PostgreSQL')

db <- dbConnect(drv, user="flame", dbname= "flame",
               host='localhost', port=5432)

FLAME_PostgreSQL(db = db, data = data, holdout = data)

dbDisconnect(db)

chiarui424/FLAME documentation built on Sept. 16, 2019, 8:43 a.m.