simCatOutMNAR: A simulated dataset 4.
In dingjshi/ALMOND: Bayesian Analysis of Local Average Treatment Effect (LATE) for Missing or/and Nonnormal Data (ALMOND)
Description
Usage
Format
Details
Examples
Description
A simulated dataset with the categorical treatment variable. The outcome variable contains
outliers and is missing not at random (MNAR, e.g., dropout or attrition).
The dataset contains a data frame with 600 rows (participants) and 4 columns (variables).
The variables are as follows.
Usage
1
Format
A data frame with 600 rows and 4 columns .
Details
outcome. The hypothetical causal outcome variable.
treatment. The hypothetical causal treatment variable.
instrument. The hypothetical instrumental variable.
mis.ind. Is the outcome variable value missing? 1=Yes, 0=No.
Examples
1
dingjshi/ALMOND documentation built on June 18, 2020, 4:32 p.m.
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Description Usage Format Details Examples
Description
A simulated dataset with the categorical treatment variable. The outcome variable contains outliers and is missing not at random (MNAR, e.g., dropout or attrition). The dataset contains a data frame with 600 rows (participants) and 4 columns (variables). The variables are as follows.
Usage
1 |
Format
A data frame with 600 rows and 4 columns .
Details
outcome. The hypothetical causal outcome variable.
treatment. The hypothetical causal treatment variable.
instrument. The hypothetical instrumental variable.
mis.ind. Is the outcome variable value missing? 1=Yes, 0=No.
Examples
1 |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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