fee_pois

Computes the first-exposure effect (FEE) for a model estimated using the
one-inflated positive Poisson distribution. The FEE represents the change in 
expected counts associated with the first exposure to treatment, relative to 
the counterfactual positive Poisson model.This function is used internally by
<code>fee</code> at given covariate values.

internal

Estimates the first-exposure effect (FEE) using a
one-inflated positive Poisson model, or a one-inflated zero-truncated
negative binomial model. In addition, estimates the marginal FEE, and
standard errors for the FEE and marginal FEE.

Ryan T. Godwin

Estimate the First-Exposure Effect (FEE) using Count Data Models

fee_pois function

<dl><dt>b</dt>
<dd>A numeric vector of estimated coefficients for the rate.</dd>
<dt>g</dt>
<dd>A numeric vector of estimated coefficients for inflation.</dd>
<dt>X</dt>
<dd>A numeric matrix of covariates for the rate.</dd>
<dt>Z</dt>
<dd>A numeric matrix of covariates for inflation.</dd></dl>

Arguments

First-Exposure Effect for One-Inflated Positive Poisson Model — fee_pois

<dl>

<dt>b</dt>
<dd>A numeric vector of estimated coefficients for the rate.</dd>


<dt>g</dt>
<dd>A numeric vector of estimated coefficients for inflation.</dd>


<dt>X</dt>
<dd>A numeric matrix of covariates for the rate.</dd>


<dt>Z</dt>
<dd>A numeric matrix of covariates for inflation.</dd>

</dl>

fee_pois: First-Exposure Effect for One-Inflated Positive Poisson Model

Description

Usage

Value

Arguments

See Also