eesim (version 0.1.0)

create_lambda: Create a series of mean outcome values

Description

Creates a vector of expected daily outcome count by relating exposure to baseline outcome values with the function: $$log(\lambda_t) = log(B_t) + log(RR)*X_t$$ where \(\lambda_t\) is the expected outcome count on day \(t\), \(B\) is the expected base outcome count on day \(t\) (incorporating long-term and seasonal trends, but not the influence of the exposure), \(RR\) is the relative risk of the outcome for a one-unit increase in exposure, and \(X_t\) is the simulated exposure on day \(t\). The user may input a custom function to relate exposure, relative risk, and baseline.

Usage

create_lambda(baseline, exposure, rr, cust_lambda_func = NULL, ...)

Arguments

baseline

A non-negative numeric vector of baseline outcome values, typically the output of create_baseline.

exposure

A numeric vector of exposure values, typically the output of sim_exposure.

rr

A non-negative numeric value specifying the relative risk (i.e., the relative risk per unit increase in the exposure).

cust_lambda_func

An R object name specifying a user-made custom function for relating baseline, relative risk, and exposure

...

Optional arguments for a custom lambda function

Value

A numeric vector of mean outcome values for each day in the simulation.

Examples

base <- create_baseline(n = 10, average_baseline = 22, trend = "linear",
                        slope = .4)
exp <- sim_exposure(n = 5, central = 100, sd = 10, amp = .6,
                    exposure_type = "continuous")
create_lambda(baseline = base, exposure = exp$x, rr = 1.01)