# Compare Groups, Analytically and Graphically cg is comprehensive data analysis software, and stands for "compare groups." Its genesis and evolution are driven by common needs to compare administrations, conditions, etc. in medicine research and development. The current version provides comparisons of unpaired samples, i.e. a linear model with one factor of at least two levels. It also provides comparisons of two paired samples. Good data graphs, modern statistical methods, and useful displays of results are emphasized. package ## Details Package: cg Type: Package Version: 1.0-3 Date: 2016-01-05 License: GPL (>= 2) LazyLoad: yes LazyData: yes Depends: R (>= 3.2.3), Hmisc (>= 3.17-1) Imports: VGAM (>= 1.0-0), methods, grDevices, graphics, stats, utils, grid, MASS, lattice, survival, multcomp, nlme, rms ## Author(s) Bill Pikounis [aut, cre, cph], John Oleynick [aut], Eva Ye [ctb] Maintainer: Bill Pikounis ## References Pikounis, B. and Oleynick, J. (2013). "The cg Package for Comparison of Groups", **Journal of Statistical Software**, Volume 52, Issue 1, 1-27, [http://www.jstatsoft.org/v52/i01/](http://www.jstatsoft.org/v52/i01/). ## Examples ```r #### One Factor data data(canine) canine.data <- prepareCGOneFactorData(canine, format="groupcolumns", analysisname="Canine", endptname="Prostate Volume", endptunits=expression(plain(cm)^3), digits=1, logscale=TRUE, refgrp="CC") ## Exploratory methods pointGraph(canine.data) boxplot(canine.data) descriptiveTable(canine.data) ## Fits and Comparisons canine.fit <- fit(canine.data) canine.comps0 <- comparisonsTable(canine.fit) errorBarGraph(canine.fit) canine.comps1 <- comparisonsTable(canine.fit, mcadjust=TRUE, type="allgroupstocontrol", refgrp="CC") comparisonsGraph(canine.comps1) grpSummaryTable(canine.fit) ## Diagnostics varianceGraph(canine.fit) qqGraph(canine.fit) downweightedTable(canine.fit, cutoff=0.95) ## Sample Size calculations canine.samplesize <- samplesizeTable(canine.fit, direction="increasing", mmdvec=c(10, 25, 50, 75, 100)) samplesizeGraph(canine.samplesize) ## Censored Data Set data(gmcsfcens) gmcsfcens.data <- prepareCGOneFactorData(gmcsfcens, format="groupcolumns", analysisname="cytokine", endptname="GM-CSF (pg/ml)", logscale=TRUE) pointGraph(gmcsfcens.data) boxplot(gmcsfcens.data) descriptiveTable(gmcsfcens.data) gmcsfcens.fit <- fit(gmcsfcens.data, type="aft") ## Paired Samples data(anorexiaFT) anorexiaFT.data <- prepareCGPairedDifferenceData(anorexiaFT, format="groupcolumns", analysisname="Anorexia FT", endptname="Weight", endptunits="lbs", expunitname="Patient", digits=1, logscale=TRUE) ## Exploratory methods descriptiveTable(anorexiaFT.data) profileGraph(anorexiaFT.data) diffGraph(anorexiaFT.data) ## Fits and Comparisons anorexiaFT.fit <- fit(anorexiaFT.data) comparisonsTable(anorexiaFT.fit) ```

cg-package