Package: testflow 1.0.2

testflow: A Workflow for Statistical Testing and Interpretation

Provides a unified workflow for choosing, running, and interpreting common statistical tests, from group comparisons and analysis of variance to regression, survival analysis, and diagnostic and agreement statistics. The package combines assumption checks, test selection, effect sizes, formatted results, plain-language interpretation, and a sample-size planning module covering continuous, binary, survival, ordinal, bioequivalence, and precision-based designs. Implemented methods follow standard references including Casella and Berger (2002, ISBN:9780534243128), Hollander et al. (2013, ISBN:9781118553299), Agresti (2013, ISBN:9780470463635), Cohen (1988, ISBN:9780805802832), Hosmer, Lemeshow and Sturdivant (2013, ISBN:9780470582473), and Julious (2010, ISBN:9781584887393).

Authors:Imad El Badisy [aut, cre]

testflow_1.0.2.tar.gz
testflow_1.0.2.zip(r-4.7-any)testflow_1.0.2.zip(r-4.6-any)testflow_1.0.2.zip(r-4.5-any)
testflow_1.0.2.tgz(r-4.6-any)testflow_1.0.2.tgz(r-4.5-any)
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testflow_1.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
testflow/json (API)

# Install 'testflow' in R:
install.packages('testflow', repos = c('https://ielbadisy.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ielbadisy/testflow/issues

On CRAN:

Conda:

data-analysisggplot2statistical-testsstatisticsteaching

5.70 score 2 stars 5 scripts 375 downloads 38 exports 69 dependencies

Last updated from:32847eae46. Checks:5 ERROR, 2 OK, 2 WARNING. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develERROR235
source / vignettesOK281
linux-releaseERROR184
macos-releaseWARNING287
macos-oldrelWARNING137
windows-develERROR109
windows-releaseERROR140
windows-oldrelERROR115
wasm-releaseOK140

Exports:as_tibblemake_cardio_datareportreport_testsample_sizesample_size_adjust_dropoutsample_size_binarysample_size_bioequivalencesample_size_cluster_adjustsample_size_continuoussample_size_ordinalsample_size_precisionsample_size_survivalsumtabSurvtest_agreementtest_categoricaltest_correlationtest_correlation_matrixtest_coxtest_diagnostictest_factorialtest_groupstest_icctest_linear_regressiontest_logistic_regressiontest_multinomialtest_one_sampletest_outlierstest_pairedtest_paired_categoricaltest_proportiontest_repeatedtest_repeated_categoricaltest_repeated_longtest_roctest_survivaltest_two_groups

Dependencies:abindbackportsbasetablebootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2gluegtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvminqamodelrnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

testflow: complete pedagogical reference
Introduction | How test selection works | Descriptive statistics | Assumption checks | One numerical variable | Two independent groups | Paired measurements | More than two groups | Post-hoc comparisons | Factorial designs | Repeated measurements (numeric) | Categorical outcomes | Association between two categorical variables | One-sample proportion | Multinomial goodness of fit | Paired categorical measurements | Repeated categorical measurements (3+ time points) | Correlation | Regression | Linear regression | Logistic regression | Survival analysis | Log-rank test | Cox proportional hazards regression | Diagnostic test accuracy and agreement | Diagnostic accuracy | ROC / AUC | Inter-rater agreement (Cohen's kappa) | Intraclass correlation coefficient | Outlier screening | Effect-size reference | Magnitude labels | Sample-size planning | Continuous endpoints | Binary endpoints | Survival endpoints | Ordinal endpoints | Bioequivalence | Precision-based sample size | Cluster-randomized adjustment and dropout | Summary of supported settings | References

Last update: 2026-09-14
Started: 2026-07-21

Sample size planning
Purpose | Continuous endpoints | Parallel superiority | Paired superiority | Repeated measures (3+ time points) | Non-inferiority and equivalence | Binary endpoints | Paired (discordant-pairs) superiority | Survival endpoints | Required events | Converting events to a total sample size | Uniform accrual | Ordinal endpoints | Bioequivalence | Precision-based sample size | Rare-prevalence planning: Wilson and exact confidence intervals | Unequal allocation for two proportions | Cluster-randomized adjustment | Dropout adjustment and reporting | Summary of supported settings | Reference

Last update: 2026-07-21
Started: 2026-07-09

Sample size: complete API reference and formulas
Purpose | sample_size_continuous() | design = "parallel" | objective = "superiority" | objective = "noninferiority" | objective = "equivalence" | design = "paired" | design = "repeated" | sample_size_binary() | objective = "superiority", method = "pooled" | objective = "superiority", method = "anticipated" | design = "paired" / design = "repeated" (n_time = 2) | sample_size_survival() | objective = "superiority", method = "exponential" | objective = "superiority", method = "ph_only" | Converting events to a total sample size | Uniform accrual | sample_size_ordinal() | sample_size_bioequivalence() | method = "iterative_tost" (default) | method = "normal_approx" | sample_size_precision() | sample_size_cluster_adjust() | sample_size() dispatcher | sample_size_adjust_dropout() | Methods on sample_size objects | References

Last update: 2026-07-21
Started: 2026-07-09

Scientific validation
Purpose | What "validated" means here | Two defects found and fixed | Bioequivalence sample size: iterative_tost was not exact | Cohen's kappa: the hypothesis test used the wrong standard error | Everything else checked, with nothing found | What this does and does not guarantee

Last update: 2026-07-21
Started: 2026-07-21

Getting started with testflow
Getting started

Last update: 2026-06-26
Started: 2026-06-12

Readme and manuals

Help Manual

Help pageTopics
Convert a testflow object to a one-row tibbleas_tibble
Simulate a small cardiovascular teaching datasetmake_cardio_data
Plot a testflow objectplot.testflow
Print a summary for a sample size objectprint.summary.sample_size
Print a testflow objectprint.testflow
Print a testflow summary tableprint.testflow_sumtab
Return a ready-to-use testflow reportreport
Return a ready-to-use testflow reportreport_test
Sample size planning for common trial designsas_tibble.sample_size plot.sample_size print.sample_size report.sample_size sample_size sample_size_adjust_dropout sample_size_binary sample_size_continuous sample_size_ordinal sample_size_survival summary.sample_size
Sample size for average bioequivalencesample_size_bioequivalence
Adjust an individually randomized sample size for cluster randomizationsample_size_cluster_adjust
Sample size for confidence-interval precisionsample_size_precision
Summarize a testflow objectsummary.testflow
Build a compact descriptive summary tablesumtab
Inter-rater agreement workflow (Cohen's kappa)test_agreement
Test association between two categorical variablestest_categorical
Test correlation between two numeric variablestest_correlation
Test a correlation matrixtest_correlation_matrix
Cox proportional hazards regression workflowtest_cox
Diagnostic test accuracy workflowtest_diagnostic
Run a factorial ANOVA workflowtest_factorial
Compare a numeric outcome across more than two groupstest_groups
Intraclass correlation coefficient workflowtest_icc
Multiple linear regression workflowtest_linear_regression
Logistic regression workflowtest_logistic_regression
Test multinomial goodness of fittest_multinomial
Test one numeric sample against a reference valuetest_one_sample
Detect numeric outlierstest_outliers
Compare paired before and after numeric measurementstest_paired
Test paired categorical measurementstest_paired_categorical
Test a one-sample proportiontest_proportion
Run a repeated-measures workflow from wide datatest_repeated
Test repeated categorical measurementstest_repeated_categorical
Run a repeated-measures workflow from long datatest_repeated_long
Receiver operating characteristic (ROC) curve workflowtest_roc
Kaplan-Meier and log-rank survival workflowtest_survival
Compare a numeric outcome between two independent groupstest_two_groups