Description Usage Arguments Details Value See Also Examples
its_llm
estimates placebo intercept shift of a time series permuting the cut-point.
1 2 | its_llm_placebo(df, rvar, outcome, trend = "none", bw, donut = 0,
nsim = 200)
|
df |
(required) |
rvar |
(required) the name of the running variable in |
outcome |
(required) the name of the outcome variable in |
trend |
include a linear term ('lin'), a quadratic term ('quad') or no trend at all ('none')? |
bw |
either a scalar or a vector of length 2 defining the bandwidth to the left (right) of the cut-point on the scale of |
donut |
either a scalar or a vector of length 2 defining the length of the period to the left (right) of the cut-point for which the data are dropped (on the scale of |
nsim |
if the number of potential placebo estimates is larger than |
Permutes the cut-point of a time series within the data points that are observed before the cut-point. The resulting distribution can be thought of as a distribution of typical shifts in the time series conditional on a selected local linear regression specification and might used as a reference distribution to make inferences about the actual estimate at the cut-point.
The function only forms placebo estimates for values of the running variable that are sufficiently enough away
from the left boundary of the time series (min(rvar)+bwL
) and the cut-point (0-bwR-donut
)
such that a local linear regression with the specified bandwidth can be estimated. Use its_plot_samples
to
visualize the implied interval from which placebo estimates are formed.
numeric
vector of placebo estimates.
1 2 3 4 5 6 7 8 9 10 11 | ## Not run:
N <- 21
time <- seq(-1,1,length.out=N)
treat <- as.numeric(time >= 0)
y <- 1 + time + treat*1 + rnorm(N,0,0.25)
df <- data.frame(y=y, time=time)
its_llm_placebo(df, rvar="time", outcome="y", bw=0.25)
## End(Not run)
|
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