cum.g weight truncation scheme and untruncated weight diagnostics

[osofr]

Hi Josh,

1. Is the weight truncation (on predicted g) performed separately for each type of AC node or is it being applied to the joint probability of all interventions at a particular time point?
   For example, given predicted probabilities for treatment node, A, and two censoring nodes, C1, C2, at particular time-point, I can truncate each of them, with minimum of the joint P(A,C1,C2) being equal to (0.01)^3 (for default gbounds) or instead, I could truncate the joint probability of (A,C1,C2), with minimum now equal to 0.01. From what I can see in the code the truncation is being applied separately to each node, am I correct?

2. Is it possible to add optional output with untruncated cum.g, along with the usual truncated cum.g? We use untruncated cumulative g as a diagnostic tool for practical positivity violations, presumably this could also be relevant to other users. Current ltmle implementation requires us to ru-run the entire ltmle algorithm to get untruncated g, it would save us a great deal of time if we could get both truncated and untruncated cum.g at once... This could be a part of some "diagnostic" mode for ltmle()...

Thanks a lot! Best,
Oleg

[joshuaschwab]

Hi Oleg,

1. Truncation of g is applied to the joint probability - see ltmle:::CalcCumG
2. That seems like a good idea, I'll add it to the next version. It may be a while before that's released, though. In the meanwhile, you could probably get it from the fit$g object returned from ltmle, although that could be a bit of a pain.
   Alternatively, you could hack it in there in ltmle:::EstimateG

  cum.g <- CalcCumG(gmat, gbounds)
  cum.g.unbounded <<- CalcCumG(gmat, c(0, 1))  #add this line to set a global variable with the unbounded cum g
  return(list(cum.g=cum.g, fit=fit))

Josh

---

From: osofr notifications@github.com
To: joshuaschwab/ltmle ltmle@noreply.github.com
Sent: Friday, May 16, 2014 3:10 PM
Subject: [ltmle] cum.g weight truncation scheme and untruncated weight diagnostics (#10)

Hi Josh,

1. Is the weight truncation (on predicted g) performed separately for each type of AC node or is it being applied to the joint probability of all interventions at a particular time point?
   For example, given predicted probabilities for treatment node, A, and two censoring nodes, C1, C2, at particular time-point, I can truncate each of them, with minimum of the joint P(A,C1,C2) being equal to (0.01)^3 (for default gbounds) or instead, I could truncate the joint probability of (A,C1,C2), with minimum now equal to 0.01. From what I can see in the code the truncation is being applied separately to each node, am I correct?
2. Is it possible to add optional output with untruncated cum.g, along with the usual truncated cum.g? We use untruncated cumulative g as a diagnostic tool for practical positivity violations, presumably this could also be relevant to other users. Current ltmle implementation requires us to ru-run the entire ltmle algorithm to get untruncated g, it would save us a great deal of time if we could get both truncated and untruncated cum.g at once... This could be a part of some "diagnostic" model for ltmle()...
   Thanks a lot! Best,
   Oleg
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