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---+ The =rms= Package for R : [[RmS][Regression Modeling Strategies]]
---++ Documentation | [[http://cran.r-project.org/web/packages/rms CRAN]]
   * Massive update for version 5.0-0 including interactive plotly graphics and advanced html tables useful with RStudio rmarkdown/knitr
   * Non-downward-compatible change: if using =latex= methods for models put this at the top of the code: options(prType='latex').  To use =html= put options(prType='html').
   * [[http://data.vanderbilt.edu/fh/R/rms/examples.html][Examples]] in an R markdown/knitr html
      * [[https://raw.githubusercontent.com/harrelfe/rms/master/inst/tests/examples.Rmd][Source code]]
   * [[https://youtu.be/EoIB_Obddrk][Video]] demonstrating =survplotp= interactive survival curves
   * [[https://www.rdocumentation.org/packages/rms Online help with executable examples]]
   * [[http://www.inside-r.org/packages/cran/rms Nicely formatted documentation]]
   * [[https://github.com/harrelfe/rms Github repository]] and its [[https://github.com/harrelfe/rms/commits/master][Changelog]]
   * [[http://www.inside-r.org/packages/cran/rms/docs/rmsOverview][Overview of the =rms= Package]]
   * [[http://cran.r-project.org/web/packages/rms/rms.pdf Manual]]
   * [[%ATTACHURL%/rms-Ex.pdf Graphics output]] of help file examples (note that columns of =anova= tables inside graphics do not line up correctly because of a font family not being available when running R CMD check)
   * [[%ATTACHURL%/refcard.pdf Reference card]] | [[%ATTACHURL%/refcardo.pdf For regular printing]]
---++ Evolution
=rms= is an R package that is a replacement for the =Design= package.   The package accompanies
FE Harrell's book _[[RmS][Regression Modeling Strategies]]_.   =rms= does not use any C level
interfaces to other packages as =Design= did to the =survival= package.  Thus =rms= will be easier to maintain.

=rms= has cleaned up graphics routines to make them more modular, to use =lattice= graphics, and to make it easier
to use =ggplot2= graphics.  Defaults for confidence bands are now gray scale-shaded polygons.   Starting with version 5.0-0 =plotly= interactive graphics and HTML output are implemented for many of the functions.

---++User-Visible Changes
The most visible change to the user is the replacement of the =plot.Design= function with the =Predict=, =plot.Predict=, and =bplot=
functions.  =plot.Predict= is used for bivariate graphics (using =lattice=), and =bplot= is used for 3-d graphics using base graphics functions
=image=, =contour=, and =persp=.  Multi-panel =lattice= graphics are usually better than 3-d graphics for showing the effects of multiple
predictors varying simultaneously.  The output of =Predict= is suitable for direct use by =lattice= (e.g., the =xyplot= function) and =ggplot2= if you don't want to use =plot.Predict=.<br>
As of version 2.2-0, the user will not longer specify predictor=. or predictor=NA when a predictor is varying over its detault range in =Predict, summary, nomogram, survplot, gendata=.  Instead, just list the predictor name in the call.  There is also a =ggplot= method.

=rms= also implements a high-level interface to the =quantreg= package through the new =Rq= function for quantile regression.

With version 3.1-0 a significant change is the addition of a =latex= argument to =print= methods for fit objects.  This causes the fit object to be typeset using !LaTeX.

Unlike =Design=, beginning with version 3.2-1 the =rms= =validate= and =calibrate= functions do not print summaries of which variables were selected if =bw= is =TRUE=.  This is left up to the print methods.

The linear predictor stored in =lrm= fit objects now uses the first intercept for proportional odds models and not the middle one.

Other new features include bootstrap nonparametric confidence bands for predicted values, simultaneous confidence bands, and simultaneous contrasts.

---+++ Example Changes Needed for Plotting Predicted Values
<highlight>
 plot(fit, x1=NA, x2=NA, ...) changed to
 p <- Predict(fit, x1, x2, ...)
 plot(p)              # ?plot.Predict for details; produces a lattice object
 print(plot(p))   # needed if using Sweave or are inside { }
 plot(p, ~ x1 | x2)
 plot(p, ~ x1 | groups='x2')
ggplot(p)

 plot(fit, .., method='image' or 'contour' or 'persp') changed to
 p <- Predict(..., np=50)        # type ?Predict for details
 bplot(p, ...)   # ?bplot for details; uses lattice graphics; can also give a formula
</highlight>
   * =datadensity= is no longer a separate function to use after the predictions are plotted; the user specifies data= to =plot.Predict= to get a rug plot, for example.
   * =Legend= was changed to =iLegend=
   * =nomogram= does not plot by default.  You must use =plot(nomogram result)= to plot, and the plotting arguments are separated into the arguments for =plot.nomogram=.
   * =survplot= defaults to conf='bands' and this now produces shaded confidence bands instead of bands made by pairs of lines
   * =Varcov= is changed to the more R-base concordant =vcov=
   * =glmD= is renamed =Glm=
   * =glsD= is renamed =Gls=
   * =Rq= allows fitting of quantile regression models with the full complement of =rms= capabilities including restricted cubic splines for covariates, restricted interaction surfaces, effect plots, bootstrap covariance estimation, and nomograms

---++Other Changes
Less visible to the user are the following changes:
   * Removed all uses of =single()= or =storage.mode= ='single'=
   * Removed all use of =.newSurvival=
   * =predictDesign= changed to =predictrms=, added ref.zero argument
   * There is no longer a generic =nomogram= function, so =nomogram.Design= was renamed =nomogram=

---++To Do
   * When bug fixed in survfit.coxph.null remove n.all stuff
   * Make =Function.rms= and =latex.rms= work when the model contains terms like rcs()*rcs() (thanks: Rob James 30Aug10)

---++ Substantial Correction to Hmisc package =fit.mult.impute= function
In May 2013 a correction was made for an upcoming release of the Hmisc package that fixes a major error in covariance matrix calculation when =fit.mult.impute= was used with =glm= .  The covariance matrix returned from =vcov= and used in a variety of other =rms= functions was incorrect, not referring to imputation-corrected estimates

---++ Recent Changes
   * See [[https://github.com/harrelfe/rms/commits/master][Changelog]]
---++ Changes in version 4.0-0 (2013-07-10)
   * Cleaned up label logic in Surv, made it work with interval2 (thanks:Chris Andrews)
   * Fixed bug in val.prob - wrong denominator for Brier score if obs removed for logistic calibration
   * Fixed inconsistency in predictrms where predict() for Cox models used a design matrix that was centered on medians and modes rather than means (thanks: David van Klaveren <d.vanklaveren.1@erasmusmc.nl>)
   * Added mean absolute prediction error to Rq output
   * Made pr argument passed to predab.resample more encompassing
   * Fixed logLik method for ols
   * Made contrast.rms and summary.rms automatically compute bootstrap nonparametric confidence limits if fit was run through bootcov
   * Fixed bug in Predict where conf.type='simultaneous' was being ignored if bootstrap coefficients were present
   * For plot.Predict made default gray scale shaded confidence bands darker
   * For bootcov exposed eps argument to fitters and default to lower value
   * Fixed bug in plot.pentrace regarding effective.df plotting
   * Added setPb function for pop-up progress bars for simulations; turn off using options(showprogress=FALSE) or options(showprogress='console')
   * Added progress bars for predab.resample (for validate, calibrate) and bootcov
   * Added bootBCa function
   * Added seed to bootcov object
   * Added boot.type='bca' to Predict, contrast.rms, summary.rms
   * Improved summary.rms to use t critical values if df.residual defined
   * Added simultaneous contrasts to summary.rms
   * Fixed calculation of Brier score, g, gp in lrm.fit by handling special case of computing linear predictor when there are no predictors in the model
   * Fixed bug in prModFit preventing successful latex'ing of penalized lrms
   * Removed \synopsis from two Rd files
   * Added prmodsel argument to predab.resample
   * Correct Rd files to change Design to rms
   * Restricted NAMESPACE to functions expected to be called by users
   * Improved Fortran code to use better dimensions for array declarations
   * Added the basic bootstrap for confidence limits for bootBCa, contrast, Predict, summary
   * Fixed bug in latex.pphsm, neatened pphsm code
   * Neatened code in rms.s
   * Improved code for bootstrapping ranks of variables in anova.rms help file
   * Fixed bug in Function.rms - undefined Nam[[i]] if strat.  Thanks: douglaswilkins@yahoo.com
   * Made quantreg be loaded at end of search list in Rq so it doesn't override latex generic in Hmisc
   * Improved plot.summary.rms to use blue of varying transparency instead of polygons to show confidence intervals, and to use only three confidence levels by default: 0.9 0.95 0.99
   * Changed Surv to Srv; use of Surv in fitting functions will result in lack of time labels and assumption of Day as time unit; no longer override Surv in survival
   * Changed calculation of Dxy (and c-index) to use survival package survConcordance service function when analyzing (censored) survival time; very fast
   * Changed default dxy to TRUE in validate.cph, validate.psm
   * Dxy is now negated if correlating Cox model log relative hazard with survival time
   * Removed dxy argument from validate.bj as it always computed
   * Added Dxy to standard output of cph, psm
   * Added help file for Srv
   * Removed reference to ps.slide from survplot help page
   * Added the general ordinal regression fitting function orm (and orm.fit) which efficiently handles thousands of intercepts because of sparse matrix representation of the information matrix; implements 5 distribution families
   * Added associated functions print.orm, vcov.orm, predict.orm, Mean.orm, Quantile.orm, latex.orm, validate.orm
   * Changed predab.resample to allow number of intercepts from resample to resample
   * Fixed bug in Mean.cph (thanks: Komal Kapoor <komal.bitsgoa@gmail.com>)
   * Removed incl.non.slopes and non.slopes arguments from all predict methods
   * Changed all functions to expect predict(..., type='x') to not return intercept columns, and all fitting functions to not store column of ones if x=TRUE
   * Changed nomogram argument intercept to kint, used default as fit$interceptRef
   * Made bootcov behave in a special way for orm, to use linear interpolation to select a single intercept targeted at median Y
   * Revamped all of rms to never store intercepts in design matrices in fit objects and to add intercepts on demand inside predictrms
   * Added new function generator !ExProb to compute exceedance probabilities from orm fits


---++ Changes in version 3.7-0 (2013-03-18)
   * Cleaned up label logic in Surv, made it work with interval2 (thanks:Chris Andrews)
   * Fixed bug in val.prob - wrong denominator for Brier score if obs removed for logistic calibration
   * Fixed inconsistency in predictrms where predict() for Cox models used a design matrix that was centered on medians and modes rather than means (thanks: David van Klaveren <d.vanklaveren.1@erasmusmc.nl>)
   * Added mean absolute prediction error to Rq output
   * Made pr argument passed to predab.resample more encompassing
   * Fixed logLik method for ols
   * Made contrast.rms and summary.rms automatically compute bootstrap nonparametric confidence limits if fit was run through bootcov
   * Fixed bug in Predict where conf.type='simultaneous' was being ignored if bootstrap coefficients were present
   * For plot.Predict made default gray scale shaded confidence bands darker
   * For bootcov exposed eps argument to fitters and default to lower value
   * Fixed bug in plot.pentrace regarding effective.df plotting
   * Added setPb function for pop-up progress bars for simulations
   * Added progress bars for predab.resample (for validate, calibrate) and bootcov
   * Added bootBCa function
   * Added seed to bootcov object
   * Added boot.type='bca' to Predict, contrast.rms, summary.rms
   * Improved summary.rms to use t critical values if df.residual defined
   * Added simultaneous contrasts to summary.rms
   * Fixed calculation of Brier score, g, gp in lrm.fit by handling special case of computing linear predictor when there are no predictors in the model
   * Fixed bug in prModFit preventing successful latex'ing of penalized lrms
   * Removed \synopsis from two Rd files
   * Added prmodsel argument to predab.resample
   * Correct Rd files to change Design to rms
   * Restricted NAMESPACE to functions expected to be called by users
   * Improved Fortran code to use better dimensions for array declarations
   * Added the basic bootstrap for confidence limits for bootBCa, contrast, Predict, summary

---++ Changes in version 3.6-3 (2013-01-11)
   * Added Li-Shepherd residuals in residuals.lrm.s, become new default (same as ordinary residuals for binary models)
   * Remove glm null fit usage as this is no longer in R

---++ Changes for version 3.6-2 (10 Dec 12)
   * bootcov, predab.resample: captured errors in all fits (to ignore bootstrap rep) using tryCatch.  Thanks: Max Gordoin <max@gforge.se>
   * predab.resample: made as.matrix(y) conditional to handle change in the survival package whereby the "type" attribute did not exist for a matrix
   * anova.rms: added new parameter vnames to allow use of variable labels instead of names in anova table; added vinfo attribute
   * residuals.lrm: removed intercept from partial residuals for binary models
   * moved comprehensive examples in rmsOverview to ~/rms/demo/all.R; greatly speeds up package checking but demo needs to be run separately for better checking, using demo(all, 'rms')
   * Fixed survfit.formula to not use .Global environment

---++ Changes for version 3.6-1 (5 Nov 12)
   * bootcov: set loglik to default to FALSE and added code to fill in missing intercepts in coef vector for prop. odds model when levels of Y not resampled; see coef.reps to default to TRUE
   * Predict: implemented fun='mean' to get proper penalty for estimating the mean function for proportional odds models
   * Added usebootcov argument to Predict to allow the user to force the use of bootstrap covariance matrix even when coef.reps=TRUE was in effect for bootcov

---++ Changes for version 3.6-0 (27 Oct 12)
   * Gls: Updated optimization calls - had become inconsistent with gls and failed if > 1 correlation parameter (thanks: Mark Seeto <markseeto@gmail.com>); removed opmeth argument
   * print.fastbw: added argument: estimates
   * survplot.survfit: handled fact that survival:::summary.survfit may not preserve order of strata levels.  Also fixed survit.cph and cph; Thanks: William.Fulp@moffitt.org
   * plot.Predict: added example showing how to rename variables in plot
   * print(fit object, latex=TRUE): added latex.naprint.delete, used new Hmisc latexDotchart function to make a dot chart of number of NAs due to each model variable if at least 4 variables have NAs
   * added trans argument to plot.anova.rms to allow transformed scales
   * Corrected cph to use model.offset(); thanks: Simon Thornley <s.thornley@auckland.ac.nz>
   * Changed latex.anova.rms to use REGRESSION instead of TOTAL label
   * Changed gendata, contrast.rms to allow expand=FALSE to prevent expand.grid from being called to generate all combinations of predictors
   * Added type= to plot.Predict to allow user to specify a different default line/point type (especially useful when x is categorical)
   * Corrected bug in offset in psm - made default offset the length of X
   * Corrected bug in calibrate.psm (fixed -> parms)
   * predab.resample, calibrate.cph, calibrate.default, calibrate.psm: stopped putting results from overall initial fit into .Global and instead had predab.resample put them in attribute keepinfo, obtained from measure() 

Changes in version 3.5-0 (2012-03-24)
   * contrast.rms: saved conf.type and conf.int in returned object, added to print method
   * Added debug= to predab.resample so user can see all the training and test sample subscripts
   * Added validate.Rq function
   * Fixed bug in Rq that caused 2 copies of fitted.values to be in fit object, which caused fit.mult.impute to double fitted.values
   * Added how to reorder predictors if using plot(Predict(fit))
   * Added new function perlcode written by Jeremy Stephens and Thomas Dupont; converts result of Function to Perl code
   * Fixed partial argument matches in many functions to pass new R checks
   * Changed matrx and DesignAssign to allow validate.Rq to consider null models; neatened code

---++ Changes for version 3.5-0 (24 Mar 12)
   * contrast.rms: saved conf.type and conf.int in returned object, added to print method
   * Added debug= to predab.resample so user can see all the training and test sample subscripts
   * Added validate.Rq function
   * Fixed bug in Rq that caused 2 copies of fitted.values to be in fit object, which caused fit.mult.impute to double fitted.values
   * Added how to reorder predictors if using plot(Predict(fit))
   * Added new function perlcode written by Jeremy Stephens and Thomas Dupont; converts result of Function to Perl code
   * Fixed partial argument matches in many functions to pass new R checks
   * Changed matrx and DesignAssign to allow validate.Rq to consider null models; neatened code

---++ Changes for version 3.4-0 (17 Jan 12)
   * psm: fixed logcorrect logic (thanks: Rob Kushler)
   * Added suggested package multcomp (required for simultaneous CLs)
   * Implemented simultaneous confidence intervals in Predict, predictrms, contrast.rms, all specific model predict methods
   * Add multiplicity adjustment for individual confidence limits computed by contrast.rms, to preserve family-wise coverage using multcomp package
   * Improved rbind.Predict to preserve order of groups as presented, as levels of .set.
   * Added example for plot.Predict showing how to suppress predictions for certain intervals/groups from being plotted
   * Added example in plot.Predict help file for graphing multiple types of confidence bands simultaneously

---++ Changes for version 3.3-3 (6 Dec 11)
   * robcov: used vcov to get var-cov matrix
   * vcov.Glm: gave precedence to $var object in fit
   * Added residuals.Glm to force call to residuals.glm, and make robcov fail as type="score" is not implemented for glm
   * Fixed bootcov for Glm to sense NA in coefficients and skip that iteration
   * Fixed digit -> digits error in latex.rms
   * Fixed f$coef error in pentrace; thanks christopher.hane@optum.com
   * Added new feature for Predict() to plot bootstrap nonparametric confidence limits if fit was run through bootcov with coef.reps=TRUE
   * Added ylim argument to plot.residuals.lrm

---++ Changes for version 3.3-2 (9 Nov 11)
   * calibrate.default: add var-cov matrix to ols objects
   * print.lrtest: discarded two formula attributes before printing
   * Added digits, size, and after arguments for latex methods for model fits, made before argument work with inline=TRUE, changed \needspace to \Needspace in latex.validate and prModFit
   * latex: fixed to consider digits for main effects
   * plot.xmean.ordinaly: added new argument cex.points
   * print.lrm: improved printing of -2 LL overall penalty
   * plot.calibrate.default: invisibly return prediction errors
   * plot.Predict: added cex.axis argument to pass to x scales; added subdata
   * print.pentrace: neatened up output
   * added title as an argument to all high-level function print methods
   * prModFit: fixed bug where Score chi2 was not translated to !LaTeX
   * prModFit: changed to use !LaTeX longtable style for coefficients etc.
   * prModFit: added arguments long and needspace
   * prModFit: suppressed title if title=""
   * rmsMisc: added nobs.rms and added nobs to object returned by logLik.rms
   * Added new argument cex.points to plot.xmean.ordinaly
   * Changed example in anova.rms to use reorder instead of reorder.factor
   * Added new argument cex.points to plot.xmean.ordinaly
   * Changed example in anova.rms to use reorder instead of reorder.factor

---++ Changes for version 3.3-1 (1 Jun 11)
   * Added new example for anova.rms for making dot plots of partial R^2 of predictors
   * Defined logLik.ols (calls logLik.lm)
   * Fixed and cleaned up logLik.rms, AIC.rms
   * Fixed residuals.psm to allow other type= values used by residuals.survreg
   * Fixed Predict and survplot.rms to allow for case where no covariates present
   * Fixed bug in val.prob where Eavg wasn't being defined if pl=FALSE (thanks: Ben Haller)
   * Fixed bug in Predict so that it could get a list or vector from predictrms
   * Fixed latex.rms to not treat * as a wild card in various contexts (may be interaction)
   * Fixed predictrms to temporarily get std.err if conf.int requested even it std.err not; omitted std.err in returned object if not wanted
   * Enhanced plot.Predict to allow plots for different predictors to be combined, after running rbind.Predict (varypred argument)
   * Also enhanced to allow groups= and cond= when varying the predictors
   * Corrected bug where sometimes would try to plot confidence limits when conf.int=FALSE was given to Predict
   * Added india, indnl arguments to anova.rms to suppress printing individual tests of interaction/nonlinearity
   * Changed anova.rms so that if all non-summary terms have (Factor+Higher Order Factor) in their labels, this part of the labels is suppressed (useful with india and indnl)


---++ Changes for version 3.3-0 (28 Feb 11)
   * In survplot.rms, fixed bug (curves were undefined if conf='bands' and labelc was FALSE)
   * In survfit.cph, fixed bug by which n wasn't always defined
   * In cph, put survival::: on exact fit call
   * Quit ignoring zlim argument in bplot; added xlabrot argument
   * Added caption argument for latex.anova.rms
   * Changed predab to not print summaries of variables selected if bw=TRUE
   * Changed predab to pass force argument to fastbw
   * fastbw: implemented force argument
   * Added force argument to validate.lrm, validate.bj, calibrate.default, calibrate.cph, calibrate.psm, validate.bj, validate.cph, validate.ols
   * print.validate: added B argument to limit how many resamples are printed summarizing variables selected if BW=TRUE
   * print.calibrate, print.calibrate.default: added B argument
   * Added latex method for results produced by validate functions
   * Fixed survest.cph to convert summary.survfit std.err to log S(t) scale
   * Fixed val.surv by pulling surv object from survest result
   * Clarified in predict.lrm help file that doesn't always use the first intercept
   * lrm.fit, lrm: linear predictor stored in fit object now uses first intercept and not middle one (NOT DOWNWARD COMPATIBLE but makes predict work when using stored linear.predictors)
   * Fixed argument consistency with validate methods


---++ Changes for version 3.2-0 (14 Feb 11)
   * Changed to be compatible with survival 2.36-3 which is now required
   * Added logLik.rms and AIC.rms functions to be compatible with standard R
   * Fixed oos.loglik.Glm
   * Fixed bootcov related to nfit='Glm'
   * Fixed (probably) old bug in latexrms with strat predictors

---++ Changes for Version 3.1-0 (12 Sep10)
   * Fixed gIndex to not use scale for labeling unless character
   * Changed default na.action in Gls to na.omit and added a note in the help file that na.delete does not work with Gls
   * Added terms component to Gls fit object (latex was not working)
   * Added examples in robcov help file testing sandwich covariance estimator
   * Added reference related to the effects package under help file for plot.Predict
   * Added more examples and simulations to gIndex
   * Fixed ancient bug in lrm.fit Fortran code to handle case where initial estimates are nearly perfect (was trying to step halve); thanks: Dan Hogan
   * Changed survdiffplot to use gray(.85) for bands instead of gray(.95)
   * Fixed formatting problem in print.psm
   * Added prStats and reVector functions to rmsMisc.s
   * Changed formatting of all print.* functions for model fits to use new prStats function
   * Added latex=TRUE option to all model fit print methods; requires !LaTeX package needspace
   * Re-wrote printing routines to make use of more general model
   * Removed long and scale options from cph printing-related routines
   * Prepare for version 2.36-1 of survival package by adding censor=FALSE argument to survfit.coxph
   * Added type="ccterms" to various predict methods
   * Made type="ccterms" the default for partial g-indexes in gIndex, i.e., combine all indirectly related (through interactions) terms
   * Added Spiegelhalter calibration test to val.prob
   * Added a check in cph to trigger an error if strata() is used in formula
   * Fixed drawing of polygon for shaded confidence bands for survplot.survfit (thanks to Patrick Breheny <patrick.breheny@uky.edu>)
   * Changed default adjust.subtitle in bplot to depend on ref.zero, thanks to David Winsemius <dwinsemius@comcast.net>
   * Used a namespace and simplified referenced to a few survival package functions that survival actually exports


---++ Changes for Version 3.0-0 (16May10)
Note: This is a major release because of the addition of new functions gIndex and !GiniMd and of the addition of the g-index to all of the regression fitters, in addition to adding type="cterms" to predict.rms
   * Made Gls not store data label() in residuals object, instead storing a label of 'Residuals'
   * Fixed handling of na.action and check for presence of offsets in Glm
   * Added type="cterms" to predict methods; computes combined terms for main effects + any interaction terms involving that main effect; in preparation for new geffects function
   * Added !GiniMd and gIndex functions
   * Change lrm (lrm.fit) to use the middle intercept in computing Brier score
   * Added 3 g-indexes to lrm fits
   * Added 1 g-index to ols, Rq, Glm, Gls fits
   * Added 2 g-indexes to cph, psm fits
   * Added g to validate.ols, .lrm, .cph, .psm, but not to validate.bj
   * Added print.validate to set default digits to 4
   * Changed validate.lrm to compute 3 indexes even on ordinal response data

---++ Changes for Version 2.2-0 (23Feb10)
   * Added levels.only option to survplot.* to remove variablename= from curve labels
   * Added digits argument to calibrate.default
   * Added new ref in val.prob help page
   * Corrected location of dataset in residuals.lrm help page (thanks frederic.holzwarth@bgc-jena.mpg.de)
   * Fixed latex.rms to latex-escape percent signs inside value labels
   * Added scat1d.opts to plot.Predict
   * Changed method of specifying variables to vary by not requiring an equals sign and a dot after the variable name, for Predict, summary, nomogram, gendata, survplot.rms
   * Added factors argument to Predict to handle the above for survplot
   * Made gendata a non-generic function, changed the order of its arguments, removed editor options, relying on R de function always
   * Thanks to Kevin Thorpe <kevin.thorpe@utoronto.ca> to make latex.summary.rms and latex.anova.rms respect the table.env argument
   * Fixed bug in calibrate.default related to digits argument
   * Re-wrote bplot to use lattice graphics (e.g., levelplot contourplot wireframe), allowing for multiple panels for 3-d plots
---++Changes for Version 2.1-0
   * Made Predict not return invisibly if predictors not specified
   * New option nlines for plot.Predict for getting line plots with 2 categorical predictors
   * Added rename option to rbind.Predict to handle case where predictor name has changed between models
   * Added ties=mean to approx( ) calls that did not have ties= specified
   * Added nlevels argument to bplot to pass to contour
   * Added par argument to iLegend - list to pass to par().
   * Redirected ... argument to iLegend to image( ).
   * Fixed groupkm - was printing warning messages wrongly
   * Added new semiparametric survival prediction calibration curve method in val.surv for external validation; this is the first implementation of smooth calibration curves for survival probability validation with right-censored data
   * Fixed calibrate confidence limits from groupkm
   * Added smooth calibration curve using hare (polspline package) for calibrate.cph and calibrate.psm
   * Added display of predicted risks for cph and psm models even for the stratified KM method (old default)


-----
   * [[CourseBios330][Full Regression Modeling Strategies course]] featuring the =rms= package
   * [[%ATTACHURL%/../RmS/rms.3day.html][Syllabus]] for a 3-day short course on the =rms= package and associated statistical methodology.
   * [[DataSets][Datasets]] for use in learning how to use =Hmisc, rms=, logistic regression, survival analysis, ordinary regression, penalized estimation, missing value imputation, data reduction, etc. (R =save()= formats)
   * [[%ATTACHURL%/../RS/sintro.pdf][An Introduction to S and the Hmisc and Design Packages]]; CF Alzola and FE Harrell (308 pages, PDF, 2004). For a list of recent changes to this document click [[%ATTACHURL%/../Hmisc/splus.changes.txt][here]].
   * [[DesignExamples][Examples of use of rms functions]] and of adapting them for special uses
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[[RmS][Go to the home page for the text REGRESSION MODELING STRATEGIES]]
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---++Bug Reports
Please see the bug reporting [[RpackagesBugs][page]]
Topic attachments
I	Attachment	Action	Size	Date	Who	Comment
pdf	refcard.pdf	manage	59.0 K	13 Sep 2009 - 09:03	FrankHarrell	Reference card for R rms package
pdf	refcardo.pdf	manage	59.2 K	13 Sep 2009 - 09:03	FrankHarrell	Reference card for rms with pages in usual order (not suitable for booklets)
pdf	rms-Ex.pdf	manage	1694.6 K	29 Dec 2011 - 22:22	FrankHarrell	Graphics output for all help file examples
Topic revision: r60 - 03 Jan 2018, FrankHarrell
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