Description Usage Arguments Value Examples
Function to create exposure history for a single time varying exposure.
1 2 | makehistory.one(input, id, times, group = NULL, exposure,
name.history = "h")
|
input |
dataframe in wide format (e.g., indexed by person) |
id |
unique observation identifier e.g. "id" |
times |
a vector of measurement times e.g. c(0,1,2) |
group |
an optional baseline variable upon which to aggregate the exposure history. This argument provides a way to adjust the metrics for a baseline covariate. For example, in the context of a trial, the grouping variable could be treatment assignment. In the context of a cohort study, this could be site e.g. "v". |
exposure |
the root name for exposure e.g. "a" |
name.history |
desired root name for time-indexed history variables e.g. "h" |
A "wide" dataframe with an added set of exposure history variables for a time-varying exposure. The new history variables will use the time-indices in the exposure vectors you supply.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | # Simulate wide data set for two subjects
id <- as.numeric(c(1, 2))
a_0 <- as.numeric(c(0, 1))
a_1 <- as.numeric(c(1, 1))
a_2 <- as.numeric(c(1, 0))
l_0 <- as.numeric(rbinom(2, 1, 0.5))
l_1 <- as.numeric(rbinom(2, 1, 0.5))
l_2 <- as.numeric(rbinom(2, 1, 0.5))
m_0 <- as.numeric(rbinom(2, 1, 0.5))
m_1 <- as.numeric(rbinom(2, 1, 0.5))
m_2 <- as.numeric(rbinom(2, 1, 0.5))
n_0 <- as.numeric(rbinom(2, 1, 0.5))
n_1 <- as.numeric(rbinom(2, 1, 0.5))
n_2 <- as.numeric(rbinom(2, 1, 0.5))
mydata.wide <- data.frame(id, a_0, a_1, a_2,
l_0, l_1, l_2,
m_0, m_1, m_2,
n_0, n_1, n_2)
# Run the makehistory.one() function
mydata.history <- makehistory.one(input=mydata.wide,
id="id",
times=c(0,1,2),
exposure="a",
name.history="h"
)
|
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