{ "_id": "6a43c36f58db26aa3c358bd3", "Package": "PITS", "Title": "Power of Interrupted Time Series (ITS) Studies", "Version": "0.1.0", "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", "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", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-30 13:20:49 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 ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-06-30 10:10:02 UTC", "RemoteUrl": "https://github.com/cran/PITS", "RemoteRef": "HEAD", "RemoteSha": "d63cf1f779e6250ca03dad4ff4624b12805e9d65", "MD5sum": "4f668051b4522e7e2b74a99d4df90996", "_user": "cran", "_type": 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"week": "2026-27", "n": 1 } ], "_tags": [ { "name": "0.1.0", "date": "2026-06-30" } ], "_stars": 0, "_contributors": [ { "user": "drdaviddelorenzo", "count": 1, "uuid": 2121511 } ], "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "followers": 614, "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 0, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/PITS" }, "_devurl": "https://github.com/drdaviddelorenzo/pits", "_searchresults": 5, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/NEWS.html", "extra/NEWS.txt", "extra/PITS.html", "extra/readme.html", "extra/readme.md", "LICENSE", "manual.pdf" ], "_cranurl": false, "_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" ] } ], "_readme": "https://github.com/cran/PITS/raw/HEAD/README.md", "_rundeps": [ "lattice", "nlme" ], "_vignettes": [ { "source": "parameter-estimation.Rmd", "filename": "parameter-estimation.html", "title": "Estimating ITS parameters from pre-intervention data", "author": "PITS package", "engine": "knitr::rmarkdown", "headings": [ "Overview", "Using individual estimation functions", "When to use individual functions", "Using the all-in-one wrapper", "Custom column names", "Diagnostic plots", "What if I have no pre-intervention data?", "Handling non-standard situations", "Date-indexed time column", "Missing values", "Very short pre-periods", "Typical parameter ranges for monthly hospital data", "References" ], "created": "2026-06-30 10:10:02", "modified": "2026-06-30 10:10:02", "commits": 1 }, { "source": "cdss-cfr-example.Rmd", "filename": "cdss-cfr-example.html", "title": "PITS: Power of an ITS — CDSS/CFR worked example", "author": "PITS package", "engine": "knitr::rmarkdown", "headings": [ "Motivating example", "Step 1 — Load pre-intervention data", "Step 2 — Estimate nuisance parameters", "Step 3 — Specify the clinical hypothesis", "Step 4 — Calculate power for a single design", "Step 5 — Optimise with a design sweep", "Step 6 — Plot a simulated ITS realisation", "Step 7 — Sensitivity analysis", "Step 8 — Multi-site analysis", "Summary table", "One-call shortcut", "References" ], "created": "2026-06-30 10:10:02", "modified": "2026-06-30 10:10:02", "commits": 1 } ], "_score": 3, "_indexed": true, "_nocasepkg": "pits", "_universes": [ "cran", "drdaviddelorenzo" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.1.0", "date": "2026-06-30T13:22:51.000Z", "distro": "resolute", "commit": "d63cf1f779e6250ca03dad4ff4624b12805e9d65", "fileid": "e7fff5da775146522a30e4d86d1942944b4f91af525b1354812b2e6a84223854", "status": "success", "check": "OK", "buildurl": 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