fepois

Fit a Poisson model with multiple group fixed effects

Transforms away factors with many levels prior to doing an OLS.
Useful for estimating linear models with multiple group fixed effects, and for
estimating linear models which uses factors with many levels as pure control variables. See Gaure (2013) <doi:10.1016/j.csda.2013.03.024>
Includes support for instrumental variables, conditional F statistics for weak instruments,
robust and multi-way clustered standard errors, as well as limited mobility bias correction (Gaure 2014 <doi:10.1002/sta4.68>).
Since version 3.0, it provides dedicated functions to estimate Poisson models.

Mauricio Vargas

Linear Group Fixed Effects

Simen Gaure

Grant McDermott

Mauricio Vargas Sepulveda

Karl Dunkle Werner

Matthieu Stigler

Daniel Lüdecke

fepois function

<dl><dt>formula</dt>
<dd>an object of class '"formula"' (or one that can be coerced to
that class): a symbolic description of the model to be fitted. Similarly to
'lm'. See Details.</dd>
<dt>data</dt>
<dd>a data frame containing the variables of the model.</dd>
<dt>offset</dt>
<dd>this can be used to specify an a priori known component
to be included in the linear predictor during fitting. This should be
<code>NULL</code> or a numeric vector or matrix of extents matching those of the
response. One or more <code><a href="/link/offset?package=lfe&version=3.1.1" data-mini-rdoc="lfe::offset">offset</a></code> terms can be included in the
formula instead or as well, and if more than one are specified their sum is
used. See <code><a href="/link/model.offset?package=lfe&version=3.1.1" data-mini-rdoc="lfe::model.offset">model.offset</a></code>.</dd>
<dt>subset</dt>
<dd>an optional vector specifying a subset of observations to be
used in the fitting process.</dd>
<dt>robust</dt>
<dd>logical value to return a robust standard error computation.</dd>
<dt>cluster</dt>
<dd>optional variable to group by and compute sandwich-type
robust standard errors. Should be a formula of the form <code>~x_j</code> or
an object that be coerced to a formula.</dd>
<dt>pseudo_rsq</dt>
<dd>logical value to return a a pseudo-R2 based on Kendall's
correlation.</dd>
<dt>tol</dt>
<dd>tolerance value for GLM convergence criteria.</dd></dl>

Arguments

Fit a Poisson model with multiple group fixed effects — fepois

<dl>

<dt>formula</dt>
<dd>an object of class '"formula"' (or one that can be coerced to
that class): a symbolic description of the model to be fitted. Similarly to
'lm'. See Details.</dd>


<dt>data</dt>
<dd>a data frame containing the variables of the model.</dd>


<dt>offset</dt>
<dd>this can be used to specify an a priori known component
to be included in the linear predictor during fitting. This should be
<code>NULL</code> or a numeric vector or matrix of extents matching those of the
response. One or more <code><a href='https://rdrr.io/r/stats/offset.html'>offset</a></code> terms can be included in the
formula instead or as well, and if more than one are specified their sum is
used. See <code><a href='https://rdrr.io/r/stats/model.extract.html'>model.offset</a></code>.</dd>


<dt>subset</dt>
<dd>an optional vector specifying a subset of observations to be
used in the fitting process.</dd>


<dt>robust</dt>
<dd>logical value to return a robust standard error computation.</dd>


<dt>cluster</dt>
<dd>optional variable to group by and compute sandwich-type
robust standard errors. Should be a formula of the form <code>~x_j</code> or
an object that be coerced to a formula.</dd>


<dt>pseudo_rsq</dt>
<dd>logical value to return a a pseudo-R2 based on Kendall's
correlation.</dd>


<dt>tol</dt>
<dd>tolerance value for GLM convergence criteria.</dd>

</dl>

fepois: Fit a Poisson model with multiple group fixed effects

Description

Usage

Arguments

See Also