Description Usage Arguments Details Value
Sensitivity to unobserved confounders with specified parameters
1 2 3 
pol 
object of class 
q 
p(u = 1  x) (see Details) 
dp 
change in logodds of treat = 1 if u = 1 (see Details) 
d0 
change in logodds of response = 1 if treat = 0 and u = 1 (see Details) 
d1 
change in logodds of response = 1 of treat = 1 and u = 1 (see Details) 
compare 
(Optional) character vector of groups to compare; the data
will be filtered such that only specified groups are compared, and the

ptreat 
(Optional) default value for probability of treatment; if
provided, it will override fitted values in 
resp_ctl 
(Optional) 
resp_trt 
(Optional) default value for probability of response = 1
given each treatment regime ( 
controls 
vector of legitimate controls to use; the ones specified within the policy object will be used if not specified 
naive_se 
logical flag, if TRUE, return std.error from naive (nonsensitivity) test, as well as std.errors from final weighted regression 
fit_fn 
string indicating the rad estimation model/procedure used.

verbose 
logical flag, if TRUE, print relevant messages for user 
debug 
logical flag, if TRUE, returns a list of results and the expanded data frame used to fit model 
... 
additional arguments to pass to 
All sensitivity parameters (q, dp, d0, d1
) can be provided in
one of three formats, determined by the length
of each argument:
length(arg) = 1
single value applied to all observations (rows)
length(arg) =
number of levels in
grouping variableeach parameter setting applied to corresponding level in group
length(arg) = nrow(pol$data)
each parameter applied to corresponding rows
Note that if compare
is specified, the
number of grouping levels is effectively the length of compare
list
of sensitized data frame and estimates
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