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edits as requested by CRAN
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DESCRIPTION

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@@ -11,7 +11,7 @@ Description: Analysis of longitudinal time-to-event or time-to-failure data.
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Estimators (IPW, MSM-IPW, GCOMP, longitudinal TMLE) adjust for measured time-varying
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confounding and informative right-censoring. Model fitting can be performed either
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with GLM or H2O-3 machine learning libraries, including the ensemble-based
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SuperLearner ("h2oEnsemble").
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SuperLearner ('h2oEnsemble').
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The exposure, monitoring and censoring variables can be coded as either binary,
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categorical or continuous. Each can be multivariate (e.g., can use more than one
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column of dummy indicators for different censoring events).

cran-comments.md

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## Update to catch pandoc error:
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* As requested, also putting 'h2oEnsemble' inside single quotes.
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* This update performs checks for pandoc availability. Addresses the test error on Solaris: https://cran.r-project.org/web/checks/check_results_stremr.html
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## Test environments:

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