custom_baseline

A numeric value specifying the number of days for which to obtain an
exposure value.

Data frame from which to pull exposure values.

A character string specifying the desired health outcome metric.
 Options are:<ul>
<li>"death"</li>
<li>"cvd"</li>
<li>"resp"</li>
</ul>(Note: These are the column names for outcome counts in the observed data.)

outcome_type

A date of the format "yyyy-mm-dd" from which to begin
pulling exposure values. Dates in the Chicago NMMAPS data set are from
1987-01-01 to 2000-12-31.

start.date

Example of a custom baseline function that can be passed to <code><a rd-options="" href="/link/eesim?package=eesim&version=0.1.0" data-mini-rdoc="eesim::eesim">eesim</a></code> or
<code><a rd-options="" href="/link/power_calc?package=eesim&version=0.1.0" data-mini-rdoc="eesim::power_calc">power_calc</a></code>.
By default, this function pulls smoothed data from the <code>chicagoNMMAPS</code> data set
in the <code>dlnm</code> package. The user may also input a different data set from which
to pull data. The function uses a smoothed function of this observed data as the
underlying baseline outcome trend in simulating data.

Provides functions to create simulated time series of environmental
exposures (e.g., temperature, air pollution) and health outcomes for use in
power analysis and simulation studies in environmental epidemiology. This
package also provides functions to evaluate the results of simulation studies
based on these simulated time series. This work was supported by a grant
from the National Institute of Environmental Health Sciences (R00ES022631) and
a fellowship from the Colorado State University Programs for Research and
Scholarly Excellence.

Brooke Anderson

eesim

Simulate and Evaluate Time Series for Environmental Epidemiology

Sarah Koehler

custom_baseline function

Example of a custom baseline function that can be passed to <code><a rd-options='' href='eesim'>eesim</a></code> or
<code><a rd-options='' href='power_calc'>power_calc</a></code>.
By default, this function pulls smoothed data from the <code>chicagoNMMAPS</code> data set
in the <code>dlnm</code> package. The user may also input a different data set from which
to pull data. The function uses a smoothed function of this observed data as the
underlying baseline outcome trend in simulating data.

custom_baseline: Pull smoothed Chicago NMMAPS health outcome data

Description

Usage

Arguments

Value

Examples