{ "_id": "6a4888d2e06c18f0a654024f", "Package": "drtmle", "Title": "Doubly-Robust Nonparametric Estimation and Inference", "Version": "1.1.2", "Authors@R": "c(\nperson(\"David\", \"Benkeser\", email = \"benkeser@emory.edu\",\nrole = c(\"aut\", \"cre\",\"cph\"),\ncomment = c(ORCID = \"0000-0002-1019-8343\")),\nperson(\"Nima\", \"Hejazi\", email = \"nhejazi@berkeley.edu\",\nrole = \"ctb\",\ncomment = c(ORCID = \"0000-0002-7127-2789\")))", "Description": "Targeted minimum loss-based estimators of counterfactual\nmeans and causal effects that are doubly-robust with respect\nboth to consistency and asymptotic normality (Benkeser et al\n(2017), ; MJ van der Laan (2014),\n).", "License": "MIT + file LICENSE", "URL": "https://github.com/benkeser/drtmle", "BugReports": "https://github.com/benkeser/drtmle/issues", "Encoding": "UTF-8", "VignetteBuilder": "knitr", "Roxygen": "list(markdown = TRUE, old_usage = TRUE, r6 = FALSE)", "RoxygenNote": "7.1.1", "Config/pak/sysreqs": "make", "Repository": "https://benkeser.r-universe.dev", "Date/Publication": "2022-12-29 16:56:27 UTC", "RemoteUrl": "https://github.com/benkeser/drtmle", "RemoteRef": "HEAD", "RemoteSha": "538a3a264c1ca984b6d88978ca7f96165f43152c", "NeedsCompilation": "no", "Packaged": { "Date": "2026-07-04 04:10:35 UTC", "User": "root" }, "Author": "David Benkeser [aut, cre, cph] (ORCID:\n),\nNima Hejazi [ctb] (ORCID: )", "Maintainer": "David Benkeser ", "_user": "benkeser", "_type": "src", "_file": "drtmle_1.1.2.tar.gz", "_fileid": "https://r2.ropensci.org/28d0414a82c918e9fbd6d6f0adb5bbc881838ee4333ce02d400bc05decc3e90f", "_filesize": 320426, "_sha256": "28d0414a82c918e9fbd6d6f0adb5bbc881838ee4333ce02d400bc05decc3e90f", "_expires": "2026-10-12T04:15:12.000Z", "_created": "2026-07-04T04:10:35.000Z", "_published": "2026-07-04T04:15:14.279Z", "_jobs": [ { "job": 85101692056, "time": 233, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "8078190986" }, { "job": 85101692017, "time": 230, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "8078190654" }, { "job": 85101692053, "time": 171, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "8078180954" }, { "job": 85101692028, "time": 178, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "8078181228" }, { "job": 85101491463, "time": 211, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "8078162715" }, { "job": 85101692012, "time": 155, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "8078181754" }, { "job": 85101692038, "time": 191, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "8078186234" }, { "job": 85101692021, "time": 188, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "8078185654" }, { "job": 85101692044, "time": 155, "config": "windows-release", "r": "4.6.1", "check": "OK", "artifact": "8078181728" } ], "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/benkeser/actions/runs/28694420565", "_status": "success", "_upstream": "https://github.com/benkeser/drtmle", "_commit": { "id": "538a3a264c1ca984b6d88978ca7f96165f43152c", "author": "David Benkeser ", "committer": "David Benkeser ", "message": "Updates for CRAN submission\n", "time": 1672332987 }, "_maintainer": { "name": "David Benkeser", "email": "benkeser@emory.edu", "login": "benkeser", "description": "Associate Professor\nEmory University \nDepartment of Biostatistics and Bioinformatics", "uuid": 17482713, "orcid": "0000-0002-1019-8343" }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5.0", "role": "Depends" }, { "package": "SuperLearner", "role": "Imports" }, { "package": "np", "role": "Imports" }, { "package": "future.apply", "role": "Imports" }, { "package": "testthat", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "gam", "role": "Suggests" }, { "package": "quadprog", "role": "Suggests" }, { "package": "nloptr", "role": "Suggests" }, { "package": "parallel", "role": "Suggests" }, { "package": "foreach", "role": "Suggests" }, { "package": "stringi", "role": "Suggests" } ], "_owner": "benkeser", "_selfowned": true, "_usedby": 1, "_updates": [], "_tags": [], "_topics": [ "causal-inference", "ensemble-learning", "iptw", "statistical-inference", "tmle" ], "_stars": 20, "_contributors": [ { "user": "benkeser", "count": 100, "uuid": 17482713 }, { "user": "nhejazi", "count": 27, "uuid": 8527276 }, { "user": "ck37", "count": 4, "uuid": 50770 }, { "user": "resekneb", "count": 2, "uuid": 115479379 } ], "_userbio": { "uuid": 17482713, "type": "user", "name": "David Benkeser", "followers": 107, "description": "Associate Professor\r\nEmory University \r\nDepartment of Biostatistics and Bioinformatics" }, "_downloads": { "count": 436, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/drtmle" }, "_mentions": 1, "_devurl": "https://github.com/benkeser/drtmle", "_searchresults": 110, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/drtmle.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "LICENSE", "manual.pdf" ], "_homeurl": "https://github.com/benkeser/drtmle", "_realowner": "benkeser", "_cranurl": true, "_releases": [ { "version": "1.0.0", "date": "2017-08-17" }, { "version": "1.0.2", "date": "2018-02-05" }, { "version": "1.0.3", "date": "2018-07-02" }, { "version": "1.0.4", "date": "2018-12-18" }, { "version": "1.0.5", "date": "2020-01-10" }, { "version": "1.1.0", "date": "2021-06-02" }, { "version": "1.1.1", "date": "2022-04-23" }, { "version": "1.1.2", "date": "2023-01-05" } ], "_exports": [ "adaptive_iptw", "ci", "drtmle", "SL.npreg", "wald_test" ], "_help": [ { "page": "adaptive_iptw", "title": "Compute asymptotically linear IPTW estimators with super learning for the propensity score", "topics": [ "adaptive_iptw" ] }, { "page": "average_est_cov_list", "title": "Helper function for averaging lists of estimates generated in the main 'for' loop of 'drtmle'", "topics": [ "average_est_cov_list" ] }, { "page": "average_ic_list", "title": "Helper function to average convergence results and drtmle influence function estimates over multiple fits", "topics": [ "average_ic_list" ] }, { "page": "ci", "title": "Compute confidence intervals for drtmle and adaptive_iptw@", "topics": [ "ci" ] }, { "page": "ci.adaptive_iptw", "title": "Confidence intervals for adaptive_iptw objects", "topics": [ "ci.adaptive_iptw" ] }, { "page": "ci.drtmle", "title": "Confidence intervals for drtmle objects", "topics": [ "ci.drtmle" ] }, { "page": "drtmle", "title": "TMLE estimate of the average treatment effect with doubly-robust inference", "topics": [ "drtmle" ] }, { "page": "estimateG", "title": "estimateG", "topics": [ "estimateG" ] }, { "page": "estimateG_loop", "title": "estimateG_loop", "topics": [ "estimateG_loop" ] }, { "page": "estimategrn", "title": "estimategrn", "topics": [ "estimategrn" ] }, { "page": "estimategrn_loop", "title": "estimategrn_loop", "topics": [ "estimategrn_loop" ] }, { "page": "estimateQ", "title": "estimateQ", "topics": [ "estimateQ" ] }, { "page": "estimateQ_loop", "title": "estimateQ_loop", "topics": [ "estimateQ_loop" ] }, { "page": "estimateQrn", "title": "estimateQrn", "topics": [ "estimateQrn" ] }, { "page": "estimateQrn_loop", "title": "estimateQrn_loop", "topics": [ "estimateQrn_loop" ] }, { "page": "eval_Diptw", "title": "Evaluate usual influence function of IPTW", "topics": [ "eval_Diptw" ] }, { "page": "eval_Diptw_g", "title": "Evaluate extra piece of the influence function for the IPTW", "topics": [ "eval_Diptw_g" ] }, { "page": "eval_Dstar", "title": "Evaluate usual efficient influence function", "topics": [ "eval_Dstar" ] }, { "page": "eval_Dstar_g", "title": "Evaluate extra piece of efficient influence function resulting from misspecification of outcome regression", "topics": [ "eval_Dstar_g" ] }, { "page": "eval_Dstar_Q", "title": "Evaluate extra piece of efficient influence function resulting from misspecification of propensity score", "topics": [ "eval_Dstar_Q" ] }, { "page": "extract_models", "title": "Help function to extract models from fitted object", "topics": [ "extract_models" ] }, { "page": "fluctuateG", "title": "fluctuateG", "topics": [ "fluctuateG" ] }, { "page": "fluctuateQ", "title": "fluctuateQ", "topics": [ "fluctuateQ" ] }, { "page": "fluctuateQ1", "title": "fluctuateQ1", "topics": [ "fluctuateQ1" ] }, { "page": "fluctuateQ2", "title": "fluctuateQ2", "topics": [ "fluctuateQ2" ] }, { "page": "make_validRows", "title": "Make list of rows in each validation fold.", "topics": [ "make_validRows" ] }, { "page": "partial_cv_preds", "title": "Helper function to properly format partially cross-validated predictions from a fitted super learner.", "topics": [ "partial_cv_preds" ] }, { "page": "plot.drtmle", "title": "Plot reduced dimension regression fits", "topics": [ "plot.drtmle" ] }, { "page": "predict.SL.npreg", "title": "Predict method for SL.npreg", "topics": [ "predict.SL.npreg" ] }, { "page": "print.adaptive_iptw", "title": "Print the output of a '\"adaptive_iptw\"' object.", "topics": [ "print.adaptive_iptw" ] }, { "page": "print.ci.adaptive_iptw", "title": "Print the output of ci.adaptive_iptw", "topics": [ "print.ci.adaptive_iptw" ] }, { "page": "print.ci.drtmle", "title": "Print the output of ci.drtmle", "topics": [ "print.ci.drtmle" ] }, { "page": "print.drtmle", "title": "Print the output of a '\"drtmle\"' object.", "topics": [ "print.drtmle" ] }, { "page": "print.wald_test.adaptive_iptw", "title": "Print the output of wald_test.adaptive_iptw", "topics": [ "print.wald_test.adaptive_iptw" ] }, { "page": "print.wald_test.drtmle", "title": "Print the output of wald_test.drtmle", "topics": [ "print.wald_test.drtmle" ] }, { "page": "reorder_list", "title": "Helper function to reorder lists according to cvFolds", "topics": [ "reorder_list" ] }, { "page": "SL.npreg", "title": "Super learner wrapper for kernel regression", "topics": [ "SL.npreg" ] }, { "page": "tmp_method.CC_LS", "title": "Temporary fix for convex combination method mean squared error Relative to existing implementation, we reduce the tolerance at which we declare predictions from a given algorithm the same as another", "topics": [ "tmp_method.CC_LS" ] }, { "page": "tmp_method.CC_nloglik", "title": "Temporary fix for convex combination method negative log-likelihood loss Relative to existing implementation, we reduce the tolerance at which we declare predictions from a given algorithm the same as another. Note that because of the way 'SuperLearner' is structure, one needs to install the optimization software separately.", "topics": [ "tmp_method.CC_nloglik" ] }, { "page": "wald_test", "title": "Wald tests for drtmle and adaptive_iptw objects", "topics": [ "wald_test" ] }, { "page": "wald_test.adaptive_iptw", "title": "Wald tests for adaptive_iptw objects", "topics": [ "wald_test.adaptive_iptw" ] }, { "page": "wald_test.drtmle", "title": "Wald tests for drtmle objects", "topics": [ "wald_test.drtmle" ] } ], "_readme": "https://github.com/benkeser/drtmle/raw/HEAD/README.md", "_rundeps": [ "bitops", "boot", "caTools", "codetools", "crs", "cubature", "cvAUC", "data.table", "digest", "foreach", "future", "future.apply", "gam", "globals", "gplots", "gtools", "iterators", "KernSmooth", "lattice", "listenv", "MASS", "Matrix", "MatrixModels", "nnls", "np", "parallelly", "quadprog", "quantreg", "Rcpp", "ROCR", "SparseM", "SuperLearner", "survival" ], "_vignettes": [ { "source": "using_drtmle.Rmd", "filename": "using_drtmle.html", "title": "drtmle: Doubly-Robust Inference in R", "author": "| David Benkeser | Emory University | Department of Biostatistics and Bioinformatics | 1518 Clifton Road, NE | Mailstop: 002-3AA | Atlanta, Georgia, 30322, U.S.A. | benkeser@emory.edu", "engine": "knitr::rmarkdown", "headings": [ "Introduction \\label", "Definition and estimators of the average treatment effect", "Parameters of interest \\label", "G-computation estimators \\label", "Inverse probability of treatment estimators \\label", "Doubly-robust estimators \\label", "Doubly-robust inference \\label", "Outcome-adaptive propensity score estimation \\label", "Implementation of doubly-robust inference \\label", "Estimating regressions \\label", "Using glm to estimate regressions", "Using SuperLearner to estimate regressions", "Reducing dependence on random seed", "Outcome-adaptive propensity score", "Arbitrary user-specified regressions", "Standard error estimation \\label", "Standard errors for TMLE", "Cross-validated standard errors", "Partially cross-validated standard errors", "Confidence intervals \\label", "Hypothesis tests \\label", "Missing data \\label", "Multi-level treatments", "Cross-validated regression estimates", "Inference for IPTW using adaptive PS estimators \\label", "Implementation of inference for adaptive IPTW", "Discussion", "Session Info" ], "created": "2017-08-15 20:54:56", "modified": "2022-04-20 13:47:06", "commits": 22 } ], "_score": 6.995635194597551, "_indexed": true, "_nocasepkg": "drtmle", "_universes": [ "benkeser" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.1.2", "date": "2026-07-04T04:13:04.000Z", "distro": "resolute", "commit": "538a3a264c1ca984b6d88978ca7f96165f43152c", "fileid": "https://r2.ropensci.org/fa2f9d577c1b89d6317223e4c4c9942d2447182dc906f199906e9d718700bac4", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benkeser/actions/runs/28694420565" }, { "r": "4.6.1", "os": "linux", "version": "1.1.2", "date": "2026-07-04T04:13:02.000Z", "distro": "resolute", "commit": "538a3a264c1ca984b6d88978ca7f96165f43152c", "fileid": "https://r2.ropensci.org/060871bcbc957910f755f584a5e492d9f889793f7a54ae829c1453378e60d95f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benkeser/actions/runs/28694420565" }, { "r": "4.5.3", "os": "mac", "version": "1.1.2", "date": "2026-07-04T04:12:32.000Z", "commit": "538a3a264c1ca984b6d88978ca7f96165f43152c", "fileid": "https://r2.ropensci.org/e4522134b75637567ef8cb49a0c096349d1b4ce8196e48e548c925955eba3a48", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benkeser/actions/runs/28694420565" }, { "r": "4.6.1", "os": "mac", "version": "1.1.2", "date": "2026-07-04T04:12:26.000Z", "commit": "538a3a264c1ca984b6d88978ca7f96165f43152c", "fileid": "https://r2.ropensci.org/832767b31fefbf79a6e1e22435f4438142aed5012baafb3f3e151a8cb0fca12e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benkeser/actions/runs/28694420565" }, { "r": "4.6.0", "os": "wasm", "version": "1.1.2", "date": "2026-07-04T04:13:30.000Z", "commit": "538a3a264c1ca984b6d88978ca7f96165f43152c", "fileid": "https://r2.ropensci.org/0aa8d03c6c52faffc295dc7d9c96237e74782e4e1958a4e01ebf8f702c6bc40e", "status": "success", "buildurl": "https://github.com/r-universe/benkeser/actions/runs/28694420565" }, { "r": "4.7.0", "os": "win", "version": "1.1.2", "date": "2026-07-04T04:12:03.000Z", "commit": "538a3a264c1ca984b6d88978ca7f96165f43152c", "fileid": "https://r2.ropensci.org/0e115bd639345ba2a9891711739dc5e55d5b7eb754a5c013b28ea60c8ec42570", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benkeser/actions/runs/28694420565" }, { "r": "4.5.3", "os": "win", "version": "1.1.2", "date": "2026-07-04T04:11:55.000Z", "commit": "538a3a264c1ca984b6d88978ca7f96165f43152c", "fileid": "https://r2.ropensci.org/b36301e61065492976ad14f5555983c6fe4a2e85e3480169e4690c9022ea6d03", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benkeser/actions/runs/28694420565" }, { "r": "4.6.1", "os": "win", "version": "1.1.2", "date": "2026-07-04T04:12:06.000Z", "commit": "538a3a264c1ca984b6d88978ca7f96165f43152c", "fileid": "https://r2.ropensci.org/f8a0cd932a682bc1c14e2e3fdcae175b39a7b0f9929e5a74be72d7175e26022f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/benkeser/actions/runs/28694420565" } ] }