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update package doc
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R/tipr-package.R

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#' @docType package
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#' @references
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#'
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#' D'Agostino McGowan, L. (2018). Improving Modern Techniques of Causal
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#' Inference: Finite Sample Performance of ATM and ATO Doubly Robust Estimators,
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#' Variance Estimation for ATO Estimators, and Contextualized Tipping Point
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#' Sensitivity Analyses for Unmeasured Confounding. PhD thesis, Vanderbilt
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#' University.
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#' D'Agostino McGowan, L, (2022). tipr: An R package for sensitivity analyses
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#' for unmeasured confounders. Journal of Open Source Software, 7(77), 4495.
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#'
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#' VanderWeele, TJ, and Peng D (2017). Sensitivity Analysis in Observational
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#' Research: Introducing the E-Value. Ann Intern Med, 167(4), 268–74.
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#'
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#' Cinelli, C, & Hazlett, C (2020). Making sense of sensitivity: Extending
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#' omitted variable bias. Journal of the Royal Statistical Society: Series B
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#' (Statistical Methodology), 82(1), 39–67.
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#'
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#' Lin, DY, Psaty, BM, & Kronmal, RA. (1998). Assessing the sensitivity
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#' of regression results to unmeasured confounders in observational studies.
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#' Biometrics, 54(3), 948–963.

man/tipr.Rd

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