bin_t {eesim}

Create a binary exposure trend vector

Description

Creates a trend vector for binary exposure data, centered at a probability p.

Usage

bin_t(n, p, trend = "no trend", slope = 1, amp = 0.01,
  start.date = "2000-01-01", custom_func = NULL, ...)

Arguments

n

A non-negative integer specifying the number of days to simulate.

p

A numeric value between 0 and 1 giving the mean probability of exposure across study days.

trend

A character string that gives the trend function to use. Options are:

• "no trend": No trend, either seasonal or long-term (default).

• "cos1": A seasonal trend only.

• "cos2": A seasonal trend with variable amplitude across years.

• "cos3": A seasonal trend with steadily decreasing amplitude over time.

• "linear": A linear long-term trend with no seasonal trend.

• "monthly": Uses a user-specified probability of exposure for each month.

slope

A numeric value specifying the slope of the trend, to be used with trend = "linear" or trend = "cos1linear".

amp

A numeric value specifying the amplitude of the seasonal trend. Must be between -.5 and .5.

start.date

A date of the format "yyyy-mm-dd" from which to begin simulating values.

custom_func

An R object specifying a customized function from which to create a trend variable. Must accept arguments n and p.

...

Optional arguments to a custom trend function

Value

A numeric vector of daily expected probability of exposure, to be used to generate binary exposure data with seasonal trends.

Examples

bin_t(n = 5, p = .3, trend = "cos1", amp = .3)