{ "_id": "6ae5b05e3d0f299392dd45bc", "Package": "PITS", "Title": "Power of Interrupted Time Series (ITS) Studies", "Version": "0.1.1", "Authors@R": "person(\"David\", \"de Lorenzo\", email = \"drdaviddelorenzo@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-2042-0961\",\naffiliation = \"UCL Great Ormond Street Institute of Child Health, London, UK; Neotree, London, UK (https://neotree.org/)\"))", "Description": "Provides tools for estimating the statistical power of\nInterrupted Time Series (ITS) designs, with a focus on\nhealthcare applications. The package supports prospective power\ncalculations before a study begins, and retrospective\nassessments of whether a completed study was adequately\npowered. It includes functions to estimate nuisance parameters\n(baseline, residual standard deviation, autocorrelation) from\ndata observed before the intervention, and to estimate power\nvia Monte Carlo simulation for single-site and multi-site\ndesigns. Utility functions for design optimisation sweeps and\npublication- ready plots are also provided.", "License": "MIT + file LICENSE", "Language": "en-GB", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "LazyData": "true", "URL": "https://github.com/drdaviddelorenzo/PITS", "BugReports": "https://github.com/drdaviddelorenzo/PITS/issues", "Config/roxygen2/version": "8.0.0", "Repository": "https://drdaviddelorenzo.r-universe.dev", "Date/Publication": "2026-07-03 11:39:57 UTC", "RemoteUrl": "https://github.com/drdaviddelorenzo/pits", "RemoteRef": "HEAD", "RemoteSha": "a6169a9f63cc8107f4f0438a31ad8b868568863b", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-31 08:37:38 UTC", "User": "root" }, "Author": "David de Lorenzo [aut, cre] (ORCID:\n, affiliation: UCL Great\nOrmond Street Institute of Child Health, London, UK; Neotree,\nLondon, UK (https://neotree.org/))", "Maintainer": "David de Lorenzo ", "_user": "drdaviddelorenzo", "_type": "src", "_file": "PITS_0.1.1.tar.gz", "_fileid": "https://r2.ropensci.org/9410683ba3c0fd9a9de8e85bc5087b73732076d83c6fd08f3a92eda3f98e18aa", "_filesize": 623538, "_sha256": "9410683ba3c0fd9a9de8e85bc5087b73732076d83c6fd08f3a92eda3f98e18aa", "_expires": "2027-02-08T09:09:48.000Z", "_created": "2026-10-31T08:37:38.000Z", "_published": "2026-10-31T09:09:50.153Z", "_upstream": "https://github.com/drdaviddelorenzo/pits", "_status": "success", "_maintainer": { "name": "David de Lorenzo", "email": "drdaviddelorenzo@gmail.com", "login": "drdaviddelorenzo", "linkedin": "in/drdaviddelorenzo", "orcid": "0000-0003-2042-0961", "twitter": "@daviddelorenzo", "description": "Passionate about unlocking the secrets of data for better health", "uuid": 2121511 }, "_jobs": [ { "job": 124491200784, "time": 135, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "13036387510" }, { "job": 124491200841, "time": 119, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "13036294083" }, { "job": 124491200823, "time": 143, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "13037910298" }, { "job": 124491200817, "time": 169, "config": "macos-release-arm64", "r": "4.6.2", "check": "OK", "artifact": "13036364488" }, { "job": 124490357996, "time": 252, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "13036408656" }, { "job": 124491200790, "time": 93, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "13036623430" }, { "job": 124491200809, "time": 85, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "13035938087" }, { "job": 124491200819, "time": 112, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "13036139288" }, { "job": 124491200797, "time": 83, "config": "windows-release-x86_64", "r": "4.6.2", "check": "OK", "artifact": "13036302621" } ], "_buildurl": "https://github.com/r-universe/drdaviddelorenzo/actions/runs/41185087525", "_commit": { "id": "a6169a9f63cc8107f4f0438a31ad8b868568863b", "author": "David de Lorenzo ", "committer": "David de Lorenzo ", "message": "Fix plot_power_heatmap() legend/xlab collision\n\nThe adequacy legend (mtext, side = 1) was hard-coded to line = 3, the same\nline R's default mgp uses for the x-axis label, so the two printed on top of\neach other. Moved the legend to line = 4.3, which clears the xlab and still\nfits inside the default bottom margin. Cosmetic only: no argument, return\nvalue, or plotted-data change.\n\nAlso gitignore Rplots.pdf (stray default-device output).\n", "time": 1783078797 }, "_distro": "resolute", "_host": "GitHub-Actions", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.0.0", "role": "Depends" }, { "package": "nlme", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "graphics", "role": "Imports" }, { "package": "grDevices", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" } ], "_owner": "drdaviddelorenzo", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2026-25", "n": 8 }, { "week": "2026-26", "n": 2 }, { "week": "2026-27", "n": 3 } ], "_tags": [ { "name": "v0.1.0", "date": "2026-06-23" } ], "_stars": 1, "_contributors": [ { "user": "drdaviddelorenzo", "count": 13, "uuid": 2121511 } ], "_userbio": { "uuid": 2121511, "type": "user", "name": "David de Lorenzo", "followers": 26, "description": "Passionate about unlocking the secrets of data for better health" }, "_downloads": { "count": 167, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/PITS" }, "_devurl": "https://github.com/drdaviddelorenzo/pits", "_searchresults": 6, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/manual.pdf", "extra/NEWS.html", "extra/NEWS.txt", "extra/PITS.html", "extra/readme.html", "extra/readme.md", "LICENSE" ], "_homeurl": "https://github.com/drdaviddelorenzo/pits", "_realowner": "drdaviddelorenzo", "_cranurl": true, "_releases": [ { "version": "0.1.0", "date": "2026-06-30" } ], "_exports": [ "build_param_grid", "calculate_power", "calculate_power_multi", "diagnose_params", "estimate_and_calculate", "estimate_baseline", "estimate_its_params", "estimate_rho", "estimate_sigma", "estimate_trend", "export_results", "fit_its_model", "interpret_power", "plot_its_example", "plot_power_curve", "plot_power_heatmap", "power_sweep", "run_its_power", "run_power_grid", "simulate_its_data", "simulate_predata", "validate_params" ], "_datasets": [ { "name": "example_cfr_data", "title": "Example pre-intervention case fatality rate data", "object": "example_cfr_data", "class": [ "data.frame" ], "fields": [ "time", "outcome" ], "rows": 24, "table": true, "tojson": true } ], "_help": [ { "page": "PITS-package", "title": "PITS: Power of Interrupted Time Series studies", "topics": [ "PITS-package", "PITS" ] }, { "page": "build_param_grid", "title": "Build a factorial parameter grid for power calculations", "topics": [ "build_param_grid" ] }, { "page": "calculate_power", "title": "Estimate statistical power for a single-site ITS design", "topics": [ "calculate_power" ] }, { "page": "calculate_power_multi", "title": "Estimate statistical power for a multi-site ITS design", "topics": [ "calculate_power_multi" ] }, { "page": "diagnose_params", "title": "Diagnostic plots for pre-intervention data", "topics": [ "diagnose_params" ] }, { "page": "estimate_and_calculate", "title": "Estimate parameters and calculate power in one step", "topics": [ "estimate_and_calculate" ] }, { "page": "estimate_baseline", "title": "Estimate baseline outcome from pre-intervention data", "topics": [ "estimate_baseline" ] }, { "page": "estimate_its_params", "title": "Estimate all ITS nuisance parameters from pre-intervention data", "topics": [ "estimate_its_params" ] }, { "page": "estimate_rho", "title": "Estimate AR(1) autocorrelation from pre-intervention data", "topics": [ "estimate_rho" ] }, { "page": "estimate_sigma", "title": "Estimate residual standard deviation from pre-intervention data", "topics": [ "estimate_sigma" ] }, { "page": "estimate_trend", "title": "Estimate pre-intervention trend from pre-intervention data", "topics": [ "estimate_trend" ] }, { "page": "example_cfr_data", "title": "Example pre-intervention case fatality rate data", "topics": [ "example_cfr_data" ] }, { "page": "export_results", "title": "Export PITS results to CSV and plain-text summary", "topics": [ "export_results" ] }, { "page": "fit_its_model", "title": "Fit a segmented regression model to an ITS dataset", "topics": [ "fit_its_model" ] }, { "page": "interpret_power", "title": "Interpret a power estimate qualitatively", "topics": [ "interpret_power" ] }, { "page": "plot_its_example", "title": "Plot a simulated ITS example", "topics": [ "plot_its_example" ] }, { "page": "plot_power_curve", "title": "Plot power as a function of post-intervention duration", "topics": [ "plot_power_curve" ] }, { "page": "plot_power_heatmap", "title": "Plot a power heatmap across two parameters", "topics": [ "plot_power_heatmap" ] }, { "page": "power_sweep", "title": "Design optimisation sweep: power across a range of n_post values", "topics": [ "power_sweep" ] }, { "page": "print.pits_power_result", "title": "Print method for PITS power results", "topics": [ "print.pits_power_result" ] }, { "page": "print.pits_sweep_result", "title": "Print method for PITS sweep results", "topics": [ "print.pits_sweep_result" ] }, { "page": "run_its_power", "title": "Full single-site ITS power workflow", "topics": [ "run_its_power" ] }, { "page": "run_power_grid", "title": "Run power calculations across a parameter grid", "topics": [ "run_power_grid" ] }, { "page": "simulate_its_data", "title": "Simulate a single ITS dataset", "topics": [ "simulate_its_data" ] }, { "page": "simulate_predata", "title": "Generate synthetic pre-intervention data", "topics": [ "simulate_predata" ] }, { "page": "summary.pits_power_result", "title": "Summary method for PITS power results", "topics": [ "summary.pits_power_result" ] }, { "page": "validate_params", "title": "Validate ITS parameter values before simulation", "topics": [ "validate_params" ] } ], 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