Appendix D — Glossary

Terms are defined as this book uses them. Where a term has a broader meaning elsewhere, the definition here is the working one, and the chapter cross-reference is where it is developed.

D.1 Reproducibility and compendia

Methods reproducibility. The property that another analyst, given your code, data, and environment, obtains your numbers. Distinct from replication, which asks whether the finding holds in new data. See Chapter 2.

Replication. Repeating a study with new data to see whether the finding recurs. A reproducible analysis can be replicated; an irreproducible one cannot even be checked. See Chapter 2.

Research compendium. A single directory holding the code, data, environment specification, and narrative for one study, organized by convention so that a stranger can navigate it. See Chapter 10.

Provenance. The record of where a data object came from and what was done to it. A query, a script, and a dated extraction note are provenance; a file named final_v3.csv is not.

Five Pillars. The layered stack this book treats as the minimum for a reproducible project: Dockerfile, renv.lock, .Rprofile, source code, and data. See Chapter 13.

D.2 Environment and dependencies

Library path. The ordered list of directories R searches for installed packages, returned by .libPaths(). R takes the first match and installs into the first entry. See Chapter 5.

renv. A package that gives a project its own library and records exact package versions in a lockfile. See Chapter 11.

Lockfile. renv.lock, the file recording every package version a project uses. It is the artifact committed to version control; the library itself is not. See Chapter 11.

snapshot() and restore(). The two halves of the renv cycle. snapshot() writes the current library state into the lockfile; restore() rebuilds a library to match a lockfile.

Docker image. A built, immutable filesystem containing an operating system, system libraries, and R. A container is a running instance of an image. See Chapter 12.

Layer caching. Docker’s reuse of unchanged build steps. Slow, stable layers belong early in a Dockerfile and fast-changing source late, so that editing the manuscript does not trigger a package reinstall. See Chapter 12.

Apptainer. A container runtime used on shared HPC systems, where Docker is usually unavailable because it requires root. See Chapter 9.

D.3 Version control

Commit. A recorded snapshot of the project with a message explaining why the change was made. See Chapter 7.

Branch. A named line of development that can diverge from main and later be merged back. See Chapter 7.

Merge conflict. The state where two branches changed the same lines and Git cannot decide which to keep. Resolved by editing the marked region and committing. See Chapter 8.

Pull request. A proposal to merge a branch, reviewed by a colleague and checked by CI before it lands. See Chapter 8.

Tag. A permanent, human-readable name for a specific commit, used here to mark submission and analysis-plan versions.

Continuous integration (CI). Automated rebuilding and testing of the project on a fresh machine at every push, which proves the analysis runs from what is in the repository rather than from the state of anyone’s laptop. See Chapter 27.

D.4 Reporting

Chunk. A block of executable code in a Quarto or R Markdown document. A fenced block without braces is displayed but not executed. See Chapter 15.

freeze. A Quarto setting that caches computed output and re-executes only when the source changes.

Cross-reference. A link such as @fig-name that resolves to a numbered figure, table, or section. An unresolved cross-reference is a build warning, not a silent failure.

spin and purl. Complementary knitr functions. spin() turns an annotated R script into a document; purl() extracts the code from a document back into a script. See Chapter 16.

Parameterized report. A document taking parameters at render time, so that one source produces a report per cohort or site. See Chapter 15.

D.5 Data wrangling

Tidy data. A layout in which each variable is a column, each observation a row, and each type of observational unit a table. See Chapter 18.

Long and wide format. Wide holds one row per subject with repeated measures across columns; long holds one row per subject-visit. Plotting and mixed models generally want long; within-subject differences are easier wide. See Chapter 18.

Pivot. The reshaping operation between the two, pivot_longer() and pivot_wider().

Factor. R’s type for a categorical variable, storing a fixed set of levels. Character is the safer type through reading, cleaning, and joining; factor is correct at modeling and plotting. See Chapter 19.

Level and reference level. The permitted values of a factor, and the one against which model coefficients are contrasted. The reference level should be chosen deliberately, not inherited from alphabetical order. See Chapter 19.

Tidy evaluation. The mechanism letting a function accept a bare column name. { col } embraces an argument; .data[[name]] takes a column name as a string. See Chapter 18.

Key. The column or columns identifying a row uniquely in a table. Verifying key uniqueness before a join is the single most useful check in this book. See Chapter 20.

Join. Combining tables on a key. inner_join keeps matched rows only; left_join keeps all rows of the left table; full_join keeps all rows of both. semi_join and anti_join filter the left table by presence in the right without adding columns. See Chapter 20.

Many-to-many relationship. A join in which the key repeats on both sides, producing the product of the matches. Usually a key error rather than an intention, which is why dplyr warns.

Anti-join audit. Using anti_join() to list the rows that failed to match, as a check on a join rather than a step in the pipeline.

D.6 Missing data

MCAR, MAR, MNAR. Missing completely at random, missing at random given observed variables, and missing not at random. The third cannot be tested from the data and requires sensitivity analysis. See Chapter 23.

Complete-case analysis. Dropping rows with any missing value in the model variables. Valid under MCAR, and it discards information and can bias estimates otherwise.

Mean imputation. Replacing missing values with the column mean. It shrinks the variance and understates uncertainty, and this book treats it as an antipattern. See Chapter 23.

Multiple imputation. Generating several completed datasets, fitting the model in each, and pooling. The between-dataset variation is the uncertainty single imputation discards.

Rubin’s rules. The formulas combining within- and between-imputation variance into one standard error.

Fraction of missing information (FMI). The share of the variance of an estimate attributable to missingness, reported alongside pooled results.

Delta adjustment. A sensitivity analysis shifting imputed values by a stated amount to probe departures from MAR.

D.7 Clinical data standards

CRF. Case report form, the instrument by which site staff record data. See Chapter 25.

SDTM. Study Data Tabulation Model, the CDISC standard for collected data, one row per observation. Immutable once locked; the statistician reads it and does not edit it. See Chapter 25.

ADaM. Analysis Data Model, the analysis-ready layer the statistician builds from SDTM, each value traceable back to it.

ADSL, ADTTE, ADAE. The subject-level, time-to-event, and adverse-event ADaM datasets.

TLF. Tables, listings, and figures: the outputs of the statistical analysis, assembled into the clinical study report.

Define-XML, aCRF, SDRG, ADRG. The metadata and documentation accompanying a submission: the machine-readable data definition, the annotated CRF, and the study and analysis data reviewer’s guides.

Transport file (XPT). The SAS transport format, version 5, required for regulatory submission and the durable interchange format between R and SAS. Each crossing can truncate variable names and lose labels, so each deserves a check. See Chapter 29.

Data lock and unblinding. The point after which the dataset does not change and treatment assignment becomes known. Everything pre-specified before it carries the study’s inferential authority. See Chapter 24.

Estimand. A precise statement of what is being estimated, including the population, endpoint, and handling of intercurrent events.

SAP. Statistical analysis plan. Drafted without data access, tagged in version control, and amended only with a dated new version. See Chapter 24.

D.8 Privacy

PHI. Protected health information, the eighteen identifier categories under the HIPAA Privacy Rule. See Chapter 3.

Safe Harbor. The de-identification method that removes those eighteen categories. The result is de-identified, not anonymous.

Quasi-identifier. A field that is not an identifier alone but becomes one in combination, such as ZIP code with date of birth and sex.

Date shifting. Offsetting every date for a patient by a constant, preserving within-patient intervals while destroying calendar time.

D.9 Testing

Unit test. A test of one function on known input. Fast, narrow, and catches helper bugs. See Chapter 26.

Integration test. A test running the whole pipeline on a small synthetic dataset. Catches composition bugs and silent filter and join errors, and has the best cost-benefit ratio for analysis code.

End-to-end test. A test running raw data through to final outputs. Slow, broad, and the last line of defense.

Snapshot test. A test comparing output against a recorded version, which detects change without asserting correctness.

Structural versus correctness assertion. Checking that a result has the right shape, against checking that it holds the right values. Only the second is a correctness test.

Tautological test. A test that passes regardless of whether the code is right, such as comparing a function’s output to itself.

D.10 Graphics

Aesthetic mapping. The assignment of a variable to a visual property such as position, color, or shape. The grammar of graphics requires the variable to be a column, which is why plotting usually wants long format. See Chapter 22.

Faceting. Splitting one plot into small multiples by a grouping variable.

Truncated axis. A y-axis not beginning at zero, which exaggerates a difference without containing a false number. See Chapter 34.

Alt text. A short description of what a figure shows, read by screen readers. Required for informative images; decorative images take an empty description instead.

D.11 Pipelines

DAG. Directed acyclic graph, the dependency structure of a pipeline. Editing one node makes everything downstream stale and nothing upstream. See Chapter 14.

Target. One node of a targets pipeline: a named object with declared dependencies, rebuilt only when those change.

D.12 Open publishing

Open educational resource (OER). A teaching work licensed to permit reuse, revision, and redistribution. Licenses forbidding derivative works do not qualify.

CC BY. The Creative Commons Attribution license, permitting adaptation and commercial use with credit. The standard recommendation for open textbooks.

DOI. Digital object identifier, a permanent citable handle for a deposited artifact. See Chapter 33.

Deposition. Placing data or code in a repository that guarantees persistence, as distinct from hosting it on a personal page or a lab server.