Calculate Variance-Covariance Matrix for MSM Parameters (calcSigma)
An internal function called by the tmleMSM function to calculate the variance-covariance matrix of the
parameter estimates based on the influence curve of the specified MSM.
calcSigma(hAV, gAVW, Y, Q, mAV, covar.MSM, covar.MSMA0, covar.MSMA1, I.V,
Delta, ub, id, family)hAV |
values used in numerator of weights applied to the estimation procedure |
gAVW |
p(A=a | V,W,T)*p(Delta=1 | A,V,W,T |
Y |
continuous or binary outcome variable |
Q |
estimated P(Y | A, V, W, T, Delta=1, typically targeted values |
mAV |
predicted values for EY1 from the MSM using the targeted estimates for psi |
covar.MSM |
covariate values used as predictors for the MSM when |
covar.MSMA0 |
covariate values used as predictors for the MSM when |
covar.MSMA1 |
covariate values used as predictors for the MSM when |
I.V |
indicator that observation is in stratum of interest |
Delta |
indicator of missing outcome. |
ub |
upper bound on weights |
id |
subject identifier |
family |
‘gaussian’ for continuous outcomes, ‘binomial’ for binary outcomes |
sigma |
influence-curve based variance-covariance matrix. See Rosenblum&vanderLaan2010 for details. |
Susan Gruber
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