summary.tmleMSM function

Summarization of the results of a call to the tmleMSM function

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

## 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.

Returns

• 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

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.

Author(s)

Susan Gruber

See Also

tmleMSM