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A simulated dataset of 500 observations based on Simulation Study I (Model 1, Case 3) of Riddles, Kim, and Im (2016). The data features a nonignorable nonresponse (NMAR) mechanism where the response probability depends on the study variable `y`.

Usage

riddles_case3

Format

A data frame with 500 rows and 4 variables:

x

Numeric. The auxiliary variable, x ~ Normal(0, 0.5).

y

Numeric. The study variable with nonignorable nonresponse. `y` contains `NA`s for nonrespondents.

y_true

Numeric. The complete, true value of `y` before missingness was introduced.

delta

Integer. The response indicator (1 = responded, 0 = nonresponse).

Source

Riddles, M. K., Kim, J. K., & Im, J. (2016). A Propensity-Score-Adjustment Method for Nonignorable Nonresponse. Journal of Survey Statistics and Methodology, 4(1), 1-31.

Details

This dataset was generated using the following model parameters (n = 500):

Density for x:

x ~ Normal(mean = 0, variance = 0.5)

Density for error:

e ~ Normal(mean = 0, variance = 0.9)

True Model (Case 3):

y_true = -1 + sin(2 * x) + e

Response Model (NMAR):

logit(pi) = 0.8 - 0.2 * y_true