Package: scan 0.61.9999

Juergen Wilbert

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

A collection of procedures for analysing, visualising, and managing single-case data. These include piecewise linear regression models, multilevel models, overlap indices ('PND', 'PEM', 'PAND', 'PET', 'tau-u', 'baseline corrected tau', 'CDC'), and randomization tests. Data preparation functions support outlier detection, handling missing values, scaling, truncation, rank transformation, and smoothing. An export function helps to generate html and latex tables in a publication friendly style. More details can be found in the online book 'Analyzing single-case data with R and scan', Juergen Wilbert (2023) <https://jazznbass.github.io/scan-Book/>.

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

scan_0.61.9999.tar.gz
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scan_0.61.9999.tgz(r-4.4-any)scan_0.61.9999.tgz(r-4.3-any)
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scan_0.61.9999.tgz(r-4.4-emscripten)scan_0.61.9999.tgz(r-4.3-emscripten)
scan.pdf |scan.html
scan/json (API)
NEWS

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

Peer review:

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

Datasets:

    On CRAN:

    6.20 score 3 stars 1 packages 59 scripts 442 downloads 47 mentions 73 exports 105 dependencies

    Last updated 3 months agofrom:12bc8a6410. Checks:OK: 3 NOTE: 4. Indexed: yes.

    TargetResultDate
    Doc / VignettesOKNov 05 2024
    R-4.5-winOKNov 05 2024
    R-4.5-linuxOKNov 05 2024
    R-4.4-winNOTENov 05 2024
    R-4.4-macNOTENov 05 2024
    R-4.3-winNOTENov 05 2024
    R-4.3-macNOTENov 05 2024

    Exports:%>%across_casesadd_l2all_casesas_scdfautocorrbatch_applybetween_smdcdccombineconvertcorrected_taudescribedesignestimate_designexportfill_missingfillmissingSCfirst_ofhplmirdis.scdflocal_regressionmoving_meanmoving_medianmplmnapoutlieroverlapoverlapSCpandpempetplmplot_randplotSCpndpower_testpower_testSCrand_testrand.testrandom_scdfrandSCranksrcirciSCread_scdfreadSCreadSC.excelrescalerSCsample_namesscdfscdf_attrscdf_attr<-select_casesselect_phasesset_dvarset_mvarset_pvarset_varsshiftshinyscansmdsmooth_casesstandardizestyle_plottau_utauUSCtrendtruncate_phasewrite_scdfwriteSC

    Dependencies:abindbackportsbase64encbigDbitopsbootbroombslibcachemcarcarDatacellrangerclicolorspacecommonmarkcowplotcpp11crayoncurlDerivdigestdoBydplyrevaluatefansifarverfastmapfontawesomeFormulafsgenericsggplot2gluegtgtablehighrhmshtmltoolshtmlwidgetsisobandjquerylibjsonlitejuicyjuicekableExtraknitrlabelinglatticelifecyclelme4magrittrmarkdownMASSMatrixMatrixModelsmblmmemoisemgcvmicrobenchmarkmimeminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigprettyunitsprogresspurrrquantregR6rappdirsRColorBrewerRcppRcppEigenreactablereactRreadxlrematchrlangrmarkdownrstudioapisassscalesSparseMstringistringrsurvivalsvglitesystemfontstibbletidyrtidyselecttinytexutf8V8vctrsviridisLitewithrxfunxml2yaml

    Readme and manuals

    Help Manual

    Help pageTopics
    Add level-2 dataadd_l2
    as_scdfas_scdf
    Creating a long format data frame from several single-case data frames (scdf).as.data.frame.scdf
    Autocorrelation for single-case dataautocorr
    Apply a function to each element in an scdf.batch_apply
    Between-Case Standardized Mean Differencebetween_smd print.sc_bcsmd
    Conservative Dual-Criterion Methodcdc
    Extract coefficients from plm/hplm objectscoef.sc_plm
    Combine single-case data framesc.scdf combine
    Convertconvert
    Baseline corrected taucorrected_tau
    Descriptive statistics for single-case datadescribe
    Generate a single-case design matrixdesign
    Estimate single-case designestimate_design
    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_plm export.sc_pnd export.sc_power export.sc_smd export.sc_trend
    Replacing missing measurement times in single-case datafill_missing
    Hierarchical piecewise linear model / piecewise regressioncoef.sc_hplm export.sc_hplm hplm print.sc_hplm
    IRD - Improvement rate differenceird print.sc_ird
    scdf objects Tests for objects of type "scdf"is.scdf
    Transform every single case of a single case data frameacross_cases all_cases first_of local_regression moving_mean moving_median transform.scdf
    Multivariate Piecewise linear model / piecewise regressionmplm print.sc_mplm
    scdf objects Removes any row with a missing valuena.omit.scdf
    Nonoverlap of all Pairsnap
    Handling outliers in single-case dataoutlier
    Overlap indices for single-case dataoverlap
    Percentage of all non-overlapping dataexport.sc_pand pand print.sc_pand
    Percent exceeding the medianpem
    Percent exceeding the trendpet
    Piecewise linear model / piecewise regressionplm
    Plot random distributionplot_rand
    (Deprecated) Plot single-case dataplot.scdf plotSC
    Percentage of non-overlapping datapnd
    Empirical power analysis for single-case datapower_test
    Print an scdfprint.scdf
    Randomization Tests for single-case datarand_test
    Single-case data generatorrandom_scdf
    Reliable change indexrci
    Load single-case data from filesread_scdf
    Samples random namessample_names
    Single case data frameas.scdf scdf scdf-class
    Select a subset of casesselect_cases
    Select and combine phases for overlap analysesselect_phases
    Set analysis variables in an scdfset_dvar set_mvar set_pvar set_vars
    A Shiny app for scanshinyscan
    Standardized mean differencessmd
    (Deprecated) Create styles for single-case data plotsstyle_plot
    Subset cases, rows, and variablessubset.scdf
    Summary function for an scdfsummary.scdf
    Tau-U for single-case dataexport.sc_tauu print.sc_tauu tau_u
    Trend analysis for single-cases datatrend
    Data outputwrite_scdf