SEQweights-class

An internal S4 class to help transfer weight statistics out of <code>internal_weights</code>

internal

Implementation of sequential trial emulation for the analysis of observational databases.
The 'SEQTaRget' software accommodates time-varying treatments and confounders, as well as binary
and failure time outcomes. 'SEQTaRget' allows to compare both static and dynamic strategies,
can be used to estimate observational analogs of intention-to-treat
and per-protocol effects, and can adjust for potential selection bias
induced by losses-to-follow-up. (Paper to come).

Ryan O'Dea

SEQTaRget

Sequential Trial Emulation

Alejandro Szmulewicz

Tom Palmer

Miguel Hernán

The President and Fellows of Harvard College 

SEQweights-class function

<dl>
<dt><code>weights</code></dt>
<dd>a data.table containing the estimated weights, either pre or post expansion</dd></dl>
<dt><code>coef.n0</code></dt>
<dd>numerator zero model</dd>
<dt><code>coef.n1</code></dt>
<dd>numerator one model</dd>
<dt><code>coef.d0</code></dt>
<dd>denominator zero model</dd>
<dt><code>coef.d1</code></dt>
<dd>denominator one model</dd>
<dt><code>coef.ncense</code></dt>
<dd>numerator censoring model</dd>
<dt><code>coef.dcense</code></dt>
<dd>denominator censoring model</dd>

Slots

An internal S4 class to help transfer weight statistics out of internal_weights — SEQweights-class

<dl>
<dt><code>weights</code></dt>
<dd>a data.table containing the estimated weights, either pre or post expansion</dd>


<dt><code>coef.n0</code></dt>
<dd>numerator zero model</dd>


<dt><code>coef.n1</code></dt>
<dd>numerator one model</dd>


<dt><code>coef.d0</code></dt>
<dd>denominator zero model</dd>


<dt><code>coef.d1</code></dt>
<dd>denominator one model</dd>


<dt><code>coef.ncense</code></dt>
<dd>numerator censoring model</dd>


<dt><code>coef.dcense</code></dt>
<dd>denominator censoring model</dd>


</dl>

SEQweights-class: An internal S4 class to help transfer weight statistics out of `internal_weights`

Description

Arguments

Slots