Description Usage Arguments Value Examples
Computes the bias corrected estimator of the difference between case probabilities or a linear combination of the difference between two regression vectors with respect to two high dimensional logistic regression models
and the corresponding standard error. It also constructs the confidence interval for the difference of case probabilities or a linear combination of the difference between the regression vectors and test
whether it is above zero or not. Here the case probability refers to the conditional probability of the binary response variable taking value 1 given the predictors are assigned to loading
.
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X1 
Design matrix for the first sample, of dimension n_1 x p 
y1 
Outcome vector for the first sample, of length n_1 
X2 
Design matrix for the second sample, of dimension n_2 x p 
y2 
Outcome vector for the second sample, of length n_2 
loading 
Loading, of length p 
weight 
The weight vector used for bias correction, of length n; if set to 
trans 
Should results for the case probability ( 
intercept 
Should intercept(s) be fitted for the initial estimators (default = 
intercept.loading 
Should intercept be included for the 
init.coef1 
Initial estimator of the first regression vector (default = 
init.coef2 
Initial estimator of the second regression vector (default = 
lambda1 
The tuning parameter in the construction of 
lambda2 
The tuning parameter in the construction of 
mu1 
The dual tuning parameter used in the construction of the first projection direction (default = 
mu2 
The dual tuning parameter used in the construction of the second projection direction (default = 
step1 
The step size used to compute 
step2 
The step size used to compute 
resol 
The factor by which 
maxiter 
Maximum number of steps along which 
alpha 
Level ofsignificance to test the null hypothesis which claims that the first case probability is not greater than the second case probability (default = 0.05) 
verbose 
Should inetrmediate message(s) be printed (default = 
prop.est 
The biascorrected estimator for the difference between case probabilities or the linear combination of the difference between two regression vectors 
se 
The standard error for the biascorrected estimator 
CI 
The confidence interval for the difference between case probabilities or the linear combination of the difference between two regression vectors 
decision 

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 28 29  A1gen < function(rho,p){
A1 < matrix(0,p,p)
for(i in 1:p){
for(j in 1:p){
A1[i,j] < rho^(abs(ij))
}
}
A1
}
n1 < 100
n2 < 100
p < 400
mu < rep(0,p)
rho < 0.5
Cov < (A1gen(rho,p))/2
beta1 < rep(0,p)
beta1[1:10] < c(1:10)/5
beta2 < rep(0,p)
beta2[1:5] < c(1:5)/10
X1 < MASS::mvrnorm(n1,mu,Cov)
X2 < MASS::mvrnorm(n2,mu,Cov)
exp_val1 < X1%*%beta1
exp_val2 < X2%*%beta2
prob1 < exp(exp_val1)/(1+exp(exp_val1))
prob2 < exp(exp_val2)/(1+exp(exp_val2))
y1 < rbinom(n1,1,prob1)
y2 < rbinom(n2,1,prob2)
loading < c(1,rep(0,(p1)))
Est < ITE_Logistic(X1 = X1, y1 = y1, X2 = X2, y2 = y2,loading = loading, trans = FALSE)

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