lagpad

Tool to assessing whether the results of a study could be influenced by
collinearity. Simulations under a given hypothesized truth regarding effects of an
exposure on the outcome are used and the resulting curves of lagged effects are
visualized. A user's manual is provided, which includes detailed examples (e.g. a
cohort study looking for windows of vulnerability to air pollution, a time series
study examining the linear association of air pollution with hospital admissions,
and a time series study examining the non-linear association between temperature and
mortality). The methods are described in Basagana and Barrera-Gomez (2021) <doi:10.1093/ije/dyab179>.

Jose Barrera-Gomez

collin

Visualization the Effects of Collinearity in Distributed Lag
Models and Other Linear Models

Xavier Basagana

lagpad function

<dl><dt>x</dt>
<dd>numeric vector to be lagged.</dd>
<dt>k</dt>
<dd>number of lags to be applied.</dd></dl>

Arguments

Function to get a vector lagged. — lagpad

<dl>

<dt>x</dt>
<dd>numeric vector to be lagged.</dd>


<dt>k</dt>
<dd>number of lags to be applied.</dd>

</dl>

lagpad: Function to get a vector lagged.

Description

Usage

Value

Arguments