summary.tmleMSM: Summarization of the results of a call to the tmleMSM...

Description Usage Arguments Details Value Author(s) See Also

View source: R/tmle.R

Description

These functions are all methods for class tmleMSM, summary.tmleMSM objects

Usage

1
2
3
4
5
6
## S3 method for class 'tmleMSM'
summary(object, ...)
## S3 method for class 'tmleMSM'
print(x, ...)
## S3 method for class 'summary.tmleMSM'
print(x, ...)

Arguments

object

an object of class tmleMSM.

x

an object of class tmleMSM for summary functions, class summary.tmleMSM for print functions.

...

currently ignored.

Details

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.

Value

estimates

matrix of MSM parameter estimates, standard errors, pvalues, upper and lower bounds on 95% confidence intervals

sigma

variance-covariance matrix

Qmodel

working model used to obtain initial estimate of Q portion of the likelihood, if glm used

Qterms

terms in the model for Q

Qcoef

coefficient of each term in model for Q

gmodel

model used to estimate treatment mechanism g

gterms

terms in the treatment mechanism model

gcoef

coefficient of each term in model for treatment mechanism

gtype

description of estimation procedure for treatment mechanism, e.g. "SuperLearner"

g.AVmodel

model used to estimate h(A,V) (or h(A,T))

g.AVterms

terms in the model for h(A,V)

g.AVcoef

coefficient of each term in model for h(A,V)

g.AVtype

description of estimation procedure for h(A,V)

g.Deltamodel

model used to estimate missingness mechanism g.Delta

g.Deltaterms

terms in the missingness mechanism model

g.Deltacoef

coefficient of each term in model for missingness mechanism

g.Deltatype

description of estimation procedure for missingness

psi.Qinit

MSM parameter estimates based on initial (untargeted) estimated Q

Author(s)

Susan Gruber

See Also

tmleMSM


tmle documentation built on Oct. 30, 2019, 9:57 a.m.