Description Usage Arguments Value Author(s) References Examples
This function implements Rosenbaum's sensitivity analysis for pair-matched observational study with general signed score test. It is faster and more flexible than the psens
function in the package rbounds
.
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d |
a vector of treatment-minus-control differences |
mm |
a vector (m, munder, mover) or a matrix, each column a vector (m, munder, mover) that indicates the U-statistic.s NULL means Wilcoxon's signed rank test. |
gamma |
a vector of sensitivity parameters (must be >= 1). |
alternative |
report p-value corresponds to the maximum ("upper") or minimum ("lower") bound |
approx.method |
how to compute the $p$-value upper bound? either "normal" approximation or random "permutations". |
score.method |
either approximate score or exact score |
tau |
a scalar, null hypothesis is the additive effect is |
num.perms |
number of Monte-Carlo simulations used to compute the sensivitiy value, if |
A list
p-values corresponding to each entry of gamma
two sided p-values
estimate of design sensitivity
test statistic
Means of the test statistic under sensivity gamma
Variances of the test statistic under sensitivity gamma
Effect size of T compared to E and V
Expectation of T under null at Gamma = 1
Paul Rosenbaum, Qingyuan Zhao
Rosenbaum, Paul R. Observational Studies. Springer New York, 2002.
Rosenbaum, P. R. (2011). A New u-Statistic with Superior Design Sensitivity in Matched Observational Studies. Biometrics, 67(3), 1017-1027.
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