PUMP (version 1.0.4)

gen_sim_data: Generate simulated multi-level data (simulation function)

Description

Generates simulated data for multi-level RCTs for pump-supported designs and models for both unobserved and observed potential outcomes.

Takes in two options:

- a pumpresult object OR

- a list of necessary data-generating parameters - the context (d_m) - Tbar (proportion assigned to treatment)

This function is beyond the main scope of calculating power, and is instead used for simulating data. For more info on use, see the simulation vignette.

Usage

gen_sim_data(
  d_m = NULL,
  param.list = NULL,
  Tbar = 0.5,
  pump.object = NULL,
  return.as.dataframe = TRUE,
  no.list = TRUE,
  include_POs = FALSE
)

Value

list; potential outcomes, covariates, observed outcomes, and treatment assignment.

Arguments

d_m

string; a single context, which is a design and model code. See pump_info() for list of choices.

param.list

list; model parameters such as ICC, R2, etc. See simulation vignette for details.

Tbar

scalar; the proportion of samples that are assigned to the treatment.

pump.object

A pumpresult object.

return.as.dataframe

TRUE means return list of dataframes, one for each outcome. FALSE means return components of the covariates, etc., in a list.

no.list

Only relevant if return.as.dataframe=TRUE. no.list=TRUE means if M=1 return the dataframe, not a list of length 1. FALSE means return a list of length 1, even if there is only 1 outcome.

include_POs

Include columns for the potential outcomes in addition to the observed outcome.

Examples

pp <- pump_power( d_m = "d3.2_m3ff2rc",
                  MTP = "BF",
                  MDES = rep( 0.10, 3 ),
                  M = 3,
                  J = 3, # number of schools/block
                  K = 21, # number RA blocks
                  nbar = 258,
                  Tbar = 0.50, # prop Tx
                  alpha = 0.05, # significance level
                  numCovar.1 = 5, numCovar.2 = 3,
                  R2.1 = 0.1, R2.2 = 0.7,
                  ICC.2 = 0.05, ICC.3 = 0.4,
                  rho = 0.4,
                  tnum = 200
)
sim.data <- gen_sim_data(pump.object = pp)