Package: scan 0.68.1

scan: Single-Case Data Analyses for Single and Multiple Baseline Designs

A collection of procedures for analysing, visualising, and managing single-case data. Multi-phase and multi-baseline designs are supported. Analysing methods include regression models (multilevel, multivariate, bayesian), between case standardised mean difference, overlap indices ('PND', 'PEM', 'PAND', 'NAP', 'PET', 'tau-u', 'IRD', 'baseline corrected tau', 'CDC'), and randomization tests. Data preparation functions support outlier detection, handling missing values, scaling, and custom transformations. An export function helps to generate html, word, and latex tables in a publication friendly style. A shiny app allows to use scan in a graphical user interface. More details can be found in the online book 'Analyzing single-case data with R and scan', Juergen Wilbert (2026) <https://jazznbass.github.io/scan-Book/>.

Authors:Juergen Wilbert [cre, aut], Timo Lueke [aut]

scan_0.68.1.tar.gz
scan_0.68.1.zip(r-4.7)scan_0.68.1.zip(r-4.6)scan_0.68.1.zip(r-4.5)
scan_0.68.1.tgz(r-4.6-any)scan_0.68.1.tgz(r-4.5-any)
scan_0.68.1.tar.gz(r-4.7-any)scan_0.68.1.tar.gz(r-4.6-any)
scan_0.68.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
scan/json (API)

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

Bug tracker:https://github.com/jazznbass/scan/issues

Pkgdown/docs site:https://jazznbass.github.io

Datasets:

On CRAN:

Conda:

6.77 score 6 stars 1 packages 88 scripts 1.1k downloads 47 mentions 80 exports 128 dependencies

Last updated from:64320bbf75. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK237
source / vignettesOK232
linux-release-x86_64OK189
macos-release-arm64OK207
macos-oldrel-arm64OK166
windows-develOK166
windows-releaseOK156
windows-oldrelOK152
wasm-releaseOK191

Exports:%>%across_casesadd_dummy_variablesadd_l2all_casesas_scdfautocorrbatch_applybetween_smdbplmcdccenter_atcombineconvertcorrected_taudescribedesignestimate_designexportfetchfill_missingfillmissingSCfirst_ofhplmimport_scdfirdis.scdflocal_regressionmoving_meanmoving_medianmplmnapoutlieroverlapoverlapSCpandpempetplmplot_randplotSCpndpower_testpower_testSCrand_testrand.testrandom_scdfrandSCranksrcirciSCread_scdfreadSCreadSC.excelrescalerowwiserSCsample_namesscdfscdf_attrscdf_attr<-select_casesselect_phasesset_dvarset_mvarset_na_atset_pvarset_varsshiftshinyscansmdsmooth_casesstandardizestyle_plottau_utauUSCtrendtruncate_phasewrite_scdfwriteSC

Dependencies:abindapebackportsbase64encbigDbitopsbootbroombslibcachemcarcarDatacellrangerclicodacolorspacecommonmarkcorpcorcowplotcpp11crayoncubaturecurlDerivdigestdoBydplyrevaluatefarverfastmapfontawesomeforecastFormulafracdifffsgenericsggplot2gluegtgtablehighrhmshtmltoolshtmlwidgetshttpuvisobandjquerylibjsonlitejuicyjuicekableExtraknitrlabelinglaterlatticelifecyclelitedownlme4lmtestmagrittrmarkdownMASSMatrixMatrixModelsMCMCglmmmemoisemgcvmimeminiUIminqamodelrnlmenloptrnnetnumDerivotelpbkrtestpillarpkgconfigprettyunitsprogresspromisespurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreactablereactRreadxlreformulasrematchrlangrmarkdownrstudioapiS7sassscalesshinysourcetoolsSparseMstringistringrsurvivalsvglitesystemfontstensorAtextshapingtibbletidyrtidyselecttimeDatetinytexurcautf8V8vctrsviridisLitewithrxfunxml2xtableyamlzoo

Readme and manuals

Help Manual

Help pageTopics
Add Dummy Variables for Piecewise Linear Modelsadd_dummy_variables
Add level-2 data to an scdfadd_l2
ANOVA Table for Piecewise Linear Modelsanova.sc_hplm anova.sc_mplm anova.sc_plm
as_scdfas_scdf
Creating a long format data frame from several single-case data frames (scdf).as.data.frame.scdf
Apply a function to each element in an scdf.batch_apply
Between-Case Standardized Mean Differencebetween_smd export.sc_bcsmd print.sc_bcsmd
Bayesian Piecewise Linear Model (bplm)bplm export.sc_bplm print.sc_bplm
Extract coefficients from plm/hplm objectscoef.sc_plm
Combine single-case data frames into one scdfc.scdf combine
Convert scdf to R codeconvert
Descriptive statistics for single-case datadescribe
Generate a single-case design matrix for multiple random single-casesdesign
Estimate single-case designestimate_design
Single-case example data setsBeretvas2008 Borckardt2014 byHeart2011 exampleA1B1A2B2 exampleA1B1A2B2_zvt exampleAB exampleABAB exampleABC exampleABC_150 exampleABC_50 exampleABC_outlier exampleAB_50 exampleAB_50.l2 exampleAB_add exampleAB_decreasing exampleAB_mpd exampleAB_score exampleAB_simple example_A24 example_atd example_data_sets example_stranger Grosche2011 Grosche2014 GruenkeWilbert2014 Huber2014 Huitema2000 Leidig2018 Leidig2018_l2 Lenz2013 Parker2007 Parker2009 Parker2009b Parker2011 Parker2011b SSDforR2017 Tarlow2017 Waddell2011
Export scan objects to html or latexexport export.scdf export.scdf_summary export.sc_desc export.sc_nap export.sc_overlap export.sc_pem export.sc_pet export.sc_pnd export.sc_power export.sc_smd export.sc_trend
Fetches elements from scan objectsfetch fetch.sc_bplm fetch.sc_hplm fetch.sc_mplm fetch.sc_plm
Replacing missing measurement points in single-case datafill_missing
Hierarchical piecewise linear model / piecewise regression for multiple casescoef.sc_hplm export.sc_hplm hplm print.sc_hplm
Import scdf – RStudio Addinimport_scdf
IRD - Improvement rate differenceexport.sc_ird ird print.sc_ird
Test for scdf objectsis.scdf
Transform every single case of a single case data frameacross_cases all_cases center_at first_of local_regression moving_mean moving_median rowwise set_na_at transform.scdf
Multivariate Piecewise linear model / piecewise regressionexport.sc_mplm mplm print.sc_mplm
Remove missing values from scdfna.omit.scdf
Nonoverlap of all Pairs (NAP)nap
Overlap indices for single-case dataoverlap
Percentage of all non-overlapping dataexport.sc_pand pand print.sc_pand
Percent exceeding the median (PEM)pem
Percent exceeding the trend (PET)pet
Piecewise linear model / piecewise regressionexport.sc_plm plm print.sc_plm
Plot random distributionplot_rand
(Deprecated) Plot single-case dataplot.scdf plotSC
Percentage of non-overlapping data (PND)pnd
Empirical power analysis for single-case datapower_test
Autocorrelation within and across phasesautocorr export.sc_ac print.sc_ac
Baseline corrected taucorrected_tau export.sc_bctau print.sc_bctau
Conservative Dual-Criterion Methodcdc export.sc_cdc print.sc_cdc
Handling outliers in single-case dataexport.sc_outlier outlier print.sc_outlier
Randomization Tests for single-case dataexport.sc_rand print.sc_rand rand_test
Print an scdfprint.scdf
Single-case data generatorrandom_scdf
Reliable change indexrci
Load single-case data from filesread_scdf
Rescales values of an scdfrescale
Samples random namessample_names
Single case data frame constructoras.scdf scdf scdf-class
Select a subset of cases from an scdfselect_cases
Select and combine phases for overlap analysesselect_phases
Set analysis variables in an scdf objectset_dvar set_mvar set_pvar set_vars
A Shiny app for scanshinyscan
Standardized mean differences for single-case datasmd
(Deprecated) Create styles for single-case data plotsstyle_plot
Subset cases, rows, and variables of an scdfsubset.scdf
Summary function for an scdf objectsummary.scdf
Tau-U for single-case dataexport.sc_tauu print.sc_tauu tau_u
Trend analysis for single-cases datatrend
Data output: Write single-case data to a .csv-filewrite_scdf