Package: autoReg 0.3.5

autoReg: Automatic Linear and Logistic Regression and Survival Analysis

Make summary tables for descriptive statistics and select explanatory variables automatically in various regression models. Support linear models, generalized linear models and cox-proportional hazard models. Generate publication-ready tables summarizing result of regression analysis and plots. The tables and plots can be exported in "HTML", "pdf('LaTex')", "docx('MS Word')" and "pptx('MS Powerpoint')" documents.

Authors:Keon-Woong Moon [aut, cre]

autoReg_0.3.5.tar.gz
autoReg_0.3.5.zip(r-4.7)autoReg_0.3.5.zip(r-4.6)autoReg_0.3.5.zip(r-4.5)
autoReg_0.3.5.tgz(r-4.6-any)autoReg_0.3.5.tgz(r-4.5-any)
autoReg_0.3.5.tar.gz(r-4.7-any)autoReg_0.3.5.tar.gz(r-4.6-any)
autoReg_0.3.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
autoReg/json (API)

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

Bug tracker:https://github.com/cardiomoon/autoreg/issues

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

Datasets:
  • anderson - Remission survival times of 42 leukemia patients
  • anderson1 - Remission survival times of 42 leukemia patients
  • anderson2 - Remission survival times of 31 leukemia patients

On CRAN:

Conda:

7.08 score 54 stars 90 scripts 994 downloads 69 exports 183 dependencies

Last updated from:388efdbb01. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK275
source / vignettesOK307
linux-release-x86_64OK269
macos-release-arm64OK144
macos-oldrel-arm64OK174
windows-develOK251
windows-releaseOK195
windows-oldrelOK176
wasm-releaseOK168

Exports:%>%addFitSummaryaddLabelDataadjustedPlotadjustedPlot2adjustedPlot2.survregas_printableautoRegautoReg_subautoRegCoxautoRegsurvregbootPredictcountGroupscoxzphplotcrr2statscrrFormuladf2flextabledrawlineexpectedPlotfilldownfind1stDupfindDupfit2finalfit2likfit2listfit2modelfit2multifit2newdatafit2statsfit2summarygazegaze_subgazeCatgazeContgetInteractiongetNgetSigVarsggcmprskggcmprsk2highlight2imputedRegis.mynumericloglogplotmaxncharmodelPlotmodelsSummarymodelsSummaryTablemy.chisq.test2my.t.test2mycphSimplemyformatmyftmysurvregSimplenum2factornum2statOEplotp2character2printdfremoveDupresidualNullresidualPlotselectsetLabelshortenshowEffectstrata2dfsurvfit2dfsurvreg2finalsurvreg2multi

Dependencies:askpassbackportsbase64encbigDbitbit64bitopsbootbroombslibcachemcardscardxcheckmateclicliprclustercmprskcodetoolscolorspacecommonmarkcpp11crayoncurldata.tabledatawizarddiagramdigestdoParalleldplyrevaluateexactRankTestsfarverfastmapflextablefontawesomefontBitstreamVerafontLiberationfontquiverforcatsforeachforeignFormulafsfuturefuture.applygdtoolsgenericsggplot2glmnetglobalsgluegridExtragtgtablegtsummaryhardhathavenhighrHmischmshtmlTablehtmltoolshtmlwidgetsinsightisobanditeratorsjanitorjomojquerylibjsonlitejuicyjuiceKernSmoothknitrlabelinglatticelavalazyevallifecyclelistenvlitedownlme4lubridatemagrittrmarkdownMASSMatrixMatrixModelsmaxstatmemoisemetsmgcvmicemimeminqamitmlmoonBookmultcompmvtnormnlmenloptrnnetnortestnumDerivofficeropensslordinalpammtoolspanparallellypatchworkpecpillarpkgconfigplotrixpolsplineprettyunitsprodlimprogressprogressrPublishpurrrquantregR6raggrangerrappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreactablereactRreadrreformulasriskRegressionrlangrmarkdownrmsrpartrstudioapiS7sandwichsassscalesscamshapesjlabelledsjmiscsnakecaseSparseMsparsevctrsSQUAREMstringistringrsurvivalsyssystemfontstextshapingTH.datatibbletidycmprsktidyrtidyselecttimechangetimeregtinytextzdbucminfutf8uuidV8vctrsviridisLitevroomwithrxfunxml2yamlzipzoo

Survival Analysis
What is survival analysis ? | Installation | Load package | Data melanoma | Survival analysis for whole group | Life table | Kaplan-Meier Plot | Cox-proportional hazard model | Hazard ratio plot : modelPlot() | Testing for proportional hazards | Disease-specific survival | Competing risk regression | Analysis of clustered data | 1. Frailty survival model | 2. Marginal approach
Rendered fromSurvival.Rmdusingknitr::rmarkdown

Last update: 2023-04-11
Started: 2021-12-29

Getting started
Installation | Load package | Main features | 1.Summarizing baseline characteristics : gaze() | For easy reproducible research : myft() | Summarizing baseline characteristics with two or more grouping variables | 2. For automatic selection of explanatory variables : autoReg() | Add univariate models to table and automatic selection of explanatory variables | Multiple imputation with mice() | Summarize regression model results in a plot : modelPlot()
Rendered fromGetting_started.Rmdusingknitr::rmarkdown

Last update: 2022-01-06
Started: 2022-01-04

Automatic Regression Modeling
Installation | Load package | Linear model with multiple variables | Selection of explanatory variable from univariable model | Stepwise backward elimination | Linear model with interaction between categorical variable | Missing data - automatic multiple imputation | Original data | Missed data | Multiple imputation
Rendered fromAutomatic_Regression_Modeling.Rmdusingknitr::rmarkdown

Last update: 2022-01-05
Started: 2022-01-04

Bootstrap Simulation for model prediction
Rendered fromBootstrap_Prediction.Rmdusingknitr::rmarkdown

Last update: 2022-01-05
Started: 2022-01-04

Statistical tests in gaze
Loading package | Statistical tests for numeric variables | 1. Comparison of two groups | (1) Parametric method | (2) Non-parametric method | (3) Performs test for normality | 2. Comparison of three or more groups | Statistical tests for categorical variables | (1) Default method : chi-squared test with continuity correction | (2) Chi-squared test without continuity correction | (3) Fisher's exact test | (4) Test for trend in proportions | Make a combining table with two or more grouping variables | Missing data analysis
Rendered fromStatiastical_test_in_gaze.Rmdusingknitr::rmarkdown

Last update: 2022-01-05
Started: 2022-01-05

Readme and manuals

Help Manual

Help pageTopics
Add model summary to an object of class gazeaddFitSummary
Add labels to dataaddLabelData
Draw an expected plotadjustedPlot
Draw predicted survival curve with an object survregadjustedPlot.survreg
Draw a survfitted plotadjustedPlot2
Draw predicted survival curve as a ggplot with an object survregadjustedPlot2.survreg
Remission survival times of 42 leukemia patientsanderson
Remission survival times of 42 leukemia patientsanderson1
Remission survival times of 31 leukemia patientsanderson2
Convert data.frame to printable formas_printable
Perform univariable and multivariable regression and stepwise backward regression automaticallyautoReg autoReg.coxph autoReg.glm autoReg.lm autoReg.survreg
Perform univariable and multivariable regression and stepwise backward regression automaticallyautoReg_sub
perform automatic regression for a class of coxphautoRegCox
perform automatic regression for a class of survregautoRegsurvreg
Whether a string vector can be converted to numericbeNumeric
Bootstrap simulation for model predictionbootPredict
Count groupscountGroups
Graphical Test of Proportional Hazardscoxzphplot
Extract statistics from an object of class crrcrr2stats
Competing Risk Regression with FormulacrrFormula
Make description for numeric summarydescNum
Convert data.frame to flextabledf2flextable
draw line characterdrawline
Draw an adjusted Plot for a numeric predictorexpectedPlot
filldown vector with lead valuefilldown
Find first duplicated positionfind1stDup
Find duplicated termfindDup
Make final model using stepwise backward eliminationfit2final
extract likelihood information with a coxph objectfit2lik
Make a list of univariable model with multivariable regression modelfit2list
Restore fit model data containing AsIs expressionsfit2model
Make multivariable regression model by selecting univariable models with p.value below thresholdfit2multi
Make a new data of mean value or most frequent valuefit2newdata
Summarize statistics with a modelfit2stats
Summarize statistics with a model or model listfit2summary
Produce table for descriptive statisticsgaze gaze.coxph gaze.data.frame gaze.formula gaze.glm gaze.lm gaze.survreg gaze.tidycrr
Summary function for categorical/continuous variablegaze_sub
Produce table for descriptive statisticsgaze.formula_sub
Summary function for categorical variablegazeCat
Summary function for continuous variablegazeCont
Get interaction data from datagetInteraction
Get number of data specified by 'name' and 'desc'getN
Get explanatory variables of a model with significance level below the thresholdgetSigVars
Draw Cumulative Incidence Curves for Competing Risksggcmprsk
Compare cumulative incidence to th Kaplan-Meier estimateggcmprsk2
Highlight a data.framehighlight2
Make a multiple imputed modelimputedReg
Decide whether a vector can be treated as a numeric variableis.mynumeric
takes the breaks as input and returns labels as outputlabel_parse
Draw log-log plotloglogplot
Return maximum character number except NAmaxnchar
Draw coefficients/odds ratio/hazard ratio plotmodelPlot
Makes table summarizing list of modelsmodelsSummary
Makes flextable summarizing list of modelsmodelsSummaryTable
Statistical test for categorical variables Statistical test for categorical variablesmy.chisq.test2
Statistical test for continuous variablesmy.t.test2
Fit Simple Proportional Hazards Regression ModelmycphSimple
Convert data.frame to printable formatmyformat
Convert data.frame into flextablemyft
Fit Simple AFT ModelmysurvregSimple
Convert a numeric column in a data.frame to a factornum2factor
Summarize numeric vector to statistical summarynum2stat
Draw an Observed vs Expected plotOEplot
Change p value to stringp2character2
S3 method print for an object of class autoRegprint.autoReg
S3 method print for an object of class gazeprint.gaze
S3 method for an class modelPlotprint.modelPlot
Print function for data.frameprintdf
Remove duplicated termremoveDup
Make a residual plot of NULL modelresidualNull
Draw a residual plot with an object of class coxphresidualPlot
restore data with factor in column namerestoreData
restore data with I() in column namerestoreData2
restore data with operator in column namerestoreData3
get opposite arithmetic operatorrevOperator
Convert numeric columns of data.frame to characterroundDf
Add label to a vectorsetLabel
Shorten an object of class gazeshorten
Show effects of covariatesshowEffect
Convert a character vector to a data.framestrata2df
Extract survival data from an object of class "survfit"survfit2df
Make final model using stepwise backward eliminationsurvreg2final
Make multivariable regression model by selecting univariable models with p.value below thresholdsurvreg2multi