estimator_ds: Extreme Value Bounds with Double Sampling

In acoppock/attrition:

Description

Extreme Value Bounds with Double Sampling

Usage

estimator_ds(Y, Z, R1, Attempt, R2, minY, maxY, strata = NULL, alpha = 0.05,
  data)

Arguments

Y	The (unquoted) outcome variable. Must be numeric.
Z	The (unquoted) assignment indicator variable. Must be numeric and take values 0 or 1.
R1	The (unquoted) initial sample respose indicator variable. Must be numeric and take values 0 or 1.
Attempt	The (unquoted) follow-up sample attempt indicator variable. Must be numeric and take values 0 or 1.
R2	The (unquoted) follow-up sample respose indicator variable. Must be numeric and take values 0 or 1.
minY	The minimum possible value of the outcome (Y) variable.
maxY	The maximum possible value of the outcome (Y) variable.
strata	A single (unquoted) variable that indicates which strata units are in.
alpha	The desired significance level. 0.05 by default.
data	A dataframe

Value

A results matrix

Examples

set.seed(343) # For reproducibility
N <- 1000

# Potential Outcomes
Y_0 <- sample(1:5, N, replace=TRUE, prob = c(0.1, 0.3, 0.3, 0.2, 0.1))
Y_1 <- sample(1:5, N, replace=TRUE, prob = c(0.1, 0.1, 0.4, 0.3, 0.1))

R1_0 <- rbinom(N, 1, prob = 0.7)
R1_1 <- rbinom(N, 1, prob = 0.8)

R2_0 <- rbinom(N, 1, prob = 0.9)
R2_1 <- rbinom(N, 1, prob = 0.95)

# Covariate
strata <- as.numeric(Y_0 > 2)

# Random Assignment
Z <- rbinom(N, 1, .5)

# Reveal Initial Sample Outcomes
R1 <- Z*R1_1 + (1-Z)*R1_0 # Initial sample response
Y_star <- Z*Y_1 + (1-Z)*Y_0 # True outcomes
Y <- Y_star
Y[R1==0] <- NA # Mask outcome of non-responders

# Conduct Double Sampling
Attempt <- rep(0, N)
Attempt[is.na(Y)] <- rbinom(sum(is.na(Y)), 1, .5)

R2 <- rep(0, N)
R2[Attempt==1] <-  (Z*R2_1 + (1-Z)*R2_0)[Attempt==1]

Y[R2==1 & Attempt==1] <- Y_star[R2==1 & Attempt==1]

df <- data.frame(Y, Z, R1, Attempt, R2, strata)

# Without post-stratification
estimator_ds(Y, Z, R1, Attempt, R2, minY=1, maxY=5, data=df)

# With post-stratification
estimator_ds(Y, Z, R1, Attempt, R2, minY=1, maxY=5, strata=strata, data=df)

acoppock/attrition documentation built on May 10, 2019, 5:11 a.m.