inline.pred

Helper Function to inline predict a fastglm object

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 

inline.pred function

<dl><dt>model</dt>
<dd>a fastglm object</dd>
<dt>newdata</dt>
<dd>filler for a .SD from data.table</dd>
<dt>params</dt>
<dd>parameter from SEQuential</dd>
<dt>type</dt>
<dd>type of prediction</dd>
<dt>case</dt>
<dd>case type: "default", "LTFU", "visit", "surv"</dd>
<dt>multi</dt>
<dd>multinomial flag</dd>
<dt>target</dt>
<dd>target level for multinomial</dd>
<dt>cache</dt>
<dd>optional formula cache from init_formula_cache</dd></dl>

Arguments

Helper Function to inline predict a fastglm object — inline.pred

<dl>

<dt>model</dt>
<dd>a fastglm object</dd>


<dt>newdata</dt>
<dd>filler for a .SD from data.table</dd>


<dt>params</dt>
<dd>parameter from SEQuential</dd>


<dt>type</dt>
<dd>type of prediction</dd>


<dt>case</dt>
<dd>case type: "default", "LTFU", "visit", "surv"</dd>


<dt>multi</dt>
<dd>multinomial flag</dd>


<dt>target</dt>
<dd>target level for multinomial</dd>


<dt>cache</dt>
<dd>optional formula cache from init_formula_cache</dd>

</dl>

inline.pred: Helper Function to inline predict a fastglm object

Description

Usage

Arguments