ntile_label

ntile_label() ranks observations in n groups, with labels

Assists in the whole process of designing and evaluating Randomized Control Trials.
Robust treatment assignment by strata/blocks, that handles misfits;
Power calculations of the minimum detectable treatment effect or minimum populations;
Balance tables of T-test of covariates;
Balance Regression: (treatment ~ all x variables) with F-test of null model;
Impact_evaluation: Impact evaluation regressions. This function
gives you the option to include control_vars, fixed effect variables,
cluster variables (for robust SE), multiple endogenous variables and
multiple heterogeneous variables (to test treatment effect heterogeneity)
summary_statistics: Function that creates a summary statistics table with statistics
rank observations in n groups: Creates a factor variable with n groups. Each group has
a min and max label attach to each category.
Athey, Susan, and Guido W. Imbens (2017) <arXiv:1607.00698>.

Isidoro Garcia-Urquieta

Assign Treatments, Power Calculations, Balances, Impact
Evaluation of Experiments

ntile_label function

<dl><dt>var</dt>
<dd>The variable wished to be ntile_label</dd>
<dt>n</dt>
<dd>rank the variable in n groups</dd>
<dt>digits</dt>
<dd>How many digits to include in the label</dd></dl>

Arguments

ntile_label() ranks observations in n groups, with labels — ntile_label

<dl>

<dt>var</dt>
<dd>The variable wished to be ntile_label</dd>


<dt>n</dt>
<dd>rank the variable in n groups</dd>


<dt>digits</dt>
<dd>How many digits to include in the label</dd>

</dl>

ntile_label: ntile_label() ranks observations in n groups, with labels

Description

Usage

Value

Arguments

Details

Examples