These functions are all methods for class tmleMSM, summary.tmleMSM objects
# S3 method for tmleMSM
summary(object, ...)
# S3 method for tmleMSM
print(x, ...)
# S3 method for summary.tmleMSM
print(x, ...)
matrix of MSM parameter estimates, standard errors, pvalues, upper and lower bounds on 95% confidence intervals
variance-covariance matrix
working model used to obtain initial estimate of Q portion of the likelihood, if glm used
terms in the model for Q
coefficient of each term in model for Q
model used to estimate treatment mechanism g
terms in the treatment mechanism model
coefficient of each term in model for treatment mechanism
description of estimation procedure for treatment mechanism, e.g. "SuperLearner"
model used to estimate h(A,V) (or h(A,T))
terms in the model for h(A,V)
coefficient of each term in model for h(A,V)
description of estimation procedure for h(A,V)
model used to estimate missingness mechanism g.Delta
terms in the missingness mechanism model
coefficient of each term in model for missingness mechanism
description of estimation procedure for missingness
MSM parameter estimates based on initial (untargeted) estimated Q
an object of class tmleMSM.
an object of class tmleMSM for summary functions, class summary.tmleMSM for print functions.
currently ignored.
Susan Gruber
print.tmleMSM prints the estimate, standard error, p-value, and 95% confidence interval only. print.summary.tmleMSM, called indirectly by entering the command summary(result) (where result has class tmleMSM), outputs additional information.
tmleMSM