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28 bpplot References Fleiss JL, Tytun A, Ury HK (1980): A simple approximation for calculating sample sizes for comparing independent proportions. Biometrics 36:343–6. Brittain E, Schlesselman JJ (1982): Optimal allocation for the comparison of proportions. Biometrics 38:1003–9. Gordon I, Watson R (1996): The myth of continuity-corrected sample size formulae. Biometrics 52:71–6. See Also samplesize.bin, chisq.test, binconf Examples bpower(.1, odds.ratio=.9, n=1000, alpha=c(.01,.05)) bpower.sim(.1, odds.ratio=.9, n=1000) bsamsize(.1, .05, power=.95) ballocation(.1, .5, n=100) # Plot power vs. n for various odds ratios (base prob.=.1) n
pplot 29 Description Producess side-by-side box-percentile plots from several vectors or a list of vectors. Usage bpplot(..., name=TRUE, main="Box-Percentile Plot", xlab="", ylab="", srtx=0) Arguments ... vectors or lists containing numeric components (e.g., the output of split). name main xlab ylab srtx character vector of names for the groups. Default is TRUE to put names on the x-axis. Such names are taken from the data vectors or the names attribute of the first argument if it is a list. Set name to FALSE to suppress names. If a character vector is supplied the names in the vector are used to label the groups. main title for the plot. x axis label. y axis label. rotation angle for x-axis labels. Default is zero. Value There are no returned values Side Effects A plot is created on the current graphics device. BACKGROUND Box-percentile plots are similiar to boxplots, except box-percentile plots supply more information about the univariate distributions. At any height the width of the irregular "box" is proportional to the percentile of that height, up to the 50th percentile, and above the 50th percentile the width is proportional to 100 minus the percentile. Thus, the width at any given height is proportional to the percent of observations that are more extreme in that direction. As in boxplots, the median, 25th and 75th percentiles are marked with line segments across the box. Author(s) Jeffrey Banfield umsfjban@bill.oscs.montana.edu Modified by F. Harrell 30Jun97 References Esty WW, Banfield J: The box-percentile plot. J Statistical Software 8 No. 17, 2003.
Page 1 and 2: Package ‘Hmisc’ April 29, 2009
Page 3 and 4: R topics documented: 3 HmiscOvervie
Page 5 and 6: abs.error.pred 5 abs.error.pred Ind
Page 7 and 8: approxExtrap 7 Examples all.is.nume
Page 9 and 10: areg 9 y xtype ytype nk B na.rm tol
Page 11 and 12: areg 11 ## Not run: # Examine overf
Page 13 and 14: aregImpute 13 Usage A print method
Page 15 and 16: aregImpute 15 burnin pr plotTrans t
Page 17 and 18: aregImpute 17 Author(s) Frank Harre
Page 19 and 20: aregImpute 19 # plot(1:100, f$imput
Page 21 and 22: inconf 21 method include.x include.
Page 23 and 24: iVar 23 spearman2(formula, data=NUL
Page 25 and 26: ootkm 25 bootkm Bootstrap Kaplan-Me
Page 27: power 27 bsamsize(p1, p2, fraction=
Page 31 and 32: ystats 31 a missing value causes th
Page 33 and 34: ciapower 33 Value Returns a vector
Page 35 and 36: cnvrt.coords 35 Arguments x y input
Page 37 and 38: combine 37 ## create a subplot with
Page 39 and 40: contents 39 contents(object, dslabe
Page 41 and 42: cpower 41 Details Value For handlin
Page 43 and 44: csv.get 43 Description Makes a vect
Page 45 and 46: curveRep 45 Value a new data frame.
Page 47 and 48: curveRep 47 extrap pr which method
Page 49 and 50: curveRep 49 Examples ## Not run: #
Page 51 and 52: cut2 51 Usage cut2(x, cuts, m, g, l
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Page 55 and 56: data.frame.create.modify.check 55 #
Page 61 and 62: dataRep 61 Usage variables, the per
Page 63 and 64: describe 63 Usage deff(y, cluster)
Page 65 and 66: describe 65 may or may not have a r
Page 67 and 68: describe 67 #get quantiles .05,.10,
Page 69 and 70: dotchart2 69 Details as.discrete co
Page 71 and 72: dropUnusedLevels 71 xaxis set to FA
Page 73 and 74: Ecdf 73 Usage Ecdf(x, ...) ## Defau
Page 75 and 76: Ecdf 75 Value for Ecdf.default an i
Page 77 and 78: equalBins 77 equalBins Multicolumn
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errbar 79 panel.first panel.last as
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event.chart 81 event.chart Flexible
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event.chart 83 or an S-Plus dates o
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event.chart 85 If "custom" is chose
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event.chart 87 subset.c) specified
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event.chart 89 Dubin, J.A., Lee, J.
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event.convert 91 # To produce more
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event.history 93 Description Usage
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event.history 95 the individual rig
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event.history 97 plot(heart.surv, y
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find.matches 99 ## S3 method for cl
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find.matches 101 # For many applica
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format.df 103 Value a character str
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format.df 105 \tabular environment
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gbayes 107 gbayes Gaussian Bayesian
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gbayes 109 sd prior pcdf delta v n1
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gbayes 111 stat
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getHdata 113 # Get the posterior de
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getZip 115 Examples ## Not run: get
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hist.data.frame 117 Author(s) Frank
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histbackback 119 Arguments Value x,
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HmiscOverview 121 ciapower cleanup.
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HmiscOverview 123 minor.tick mtitle
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HmiscOverview 125 sys tex transace
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hoeffd 127 Usage hoeffd(x) hoeffd(x
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html 129 file name of the file to c
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inc-dec 131 Value object ... ignore
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labcurve 133 To add a legend defini
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labcurve 135 y for putKeyEmpty and
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labcurve 137 lwd col. col transpare
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labcurve 139 Value key is called on
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label 141 # Use the mouse to draw a
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label 143 Arguments x Value self un
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latex 145 Details A.ttributes of th
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latex 147 caption=NULL, caption.lot
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latex 149 cgroup n.cgroup rgroup n.
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latex 151 booktabs table.env here l
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latex 153 PATH=paste(Sys.getenv("PA
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ldBands 155 Usage Lan. Such stoppin
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ldBands 157 Value A list of class "
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makeNstr 159 Arguments struct depth
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mChoice 161 Value For mApply, the r
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mChoice 163 table a vector (mChoice
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mdb.get 165 # could also do: # summ
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mgp.axis 167 Arguments side at see
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mhgr 169 Author(s) Frank E Harrell
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Misc 171 Author(s) Frank Harrell De
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Misc 173 outerText(string, y, setAs
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mtitle 175 set.seed(1) whichClosest
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na.detail.response 177 Usage na.del
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na.keep 179 # age=NA age!=NA sex!=N
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panel.bpplot 181 Examples nstr(c("a
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panel.bpplot 183 Author(s) Frank Ha
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pc1 185 See Also split Examples a
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plsmo 187 plsmo Plot smoothed estim
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plsmo 189 type pch cex font set to
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print.char.list 191 Value a list co
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print.char.matrix 193 print.char.ma
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ps.slide 195 Arguments x txt any ob
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ps.slide 197 strip.blank =TRUE, lty
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ps.slide 199 Value ratio lref psref
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corr 201 Details Certain functions
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corr.cens 203 Usage rcorr.cens(x, S
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corrp.cens 205 abline(h=.5, v=0, co
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cspline.eval 207 rcspline.eval Rest
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cspline.plot 209 nk knots show adj
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cspline.restate 211 after begin nbe
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edun 213 minfreq iterms pc pr For a
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equirePackage 215 Examples x
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eShape 217 colvar base reps times t
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legend 219 # d
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m.boot 221 rm.boot Bootstrap Repeat
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m.boot 223 smoother xlab xlim ylim
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m.boot 225 Details Value ordered by
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m.boot 227 n
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samplesize.bin 229 Description Give
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sasxport.get 231 Usage used, it is
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Save 233 # output; # format d1 mmdd
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scat1d 235 jitter2.default for vect
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scat1d 237 lwd col y curve line wid
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scat1d 239 Details For scat1d the l
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score.binary 241 # datadensity.data
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sedit 243 substring2(text, first, l
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show.pch 245 x
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smean.sd 247 smean.sd Compute Summa
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somers2 249 Arguments a b tol a squ
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spower 251 Usage The Weibull2 funct
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spower 253 Value spower returns the
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spss.get 255 set.seed(211) spower(r
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stata.get 257 Arguments x an unquot
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store 259 store Store an Object Per
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string.break.line 261 Value rows co
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subplot 263 subplot Embed a new plo
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summarize 265 Usage summarize store
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summarize 267 dfr
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summary.formula 269 summary.formula
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summary.formula 271 rowlabel = '',
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summary.formula 273 overall continu
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summary.formula 275 dotfont font fo
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summary.formula 277 subtitles capti
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summary.formula 279 bpplt() # annot
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summary.formula 281 y
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symbol.freq 283 summary(age ~ stage
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t.test.cluster 285 Side Effects exe
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transace 287 against the lowest lev
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transace 289 categorical binary pl
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transace 291 Details Value As trans
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transace 293 newdat
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transcan 295 values of the target v
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transcan 297 ## S3 method for class
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transcan 299 impcat mincut inverse
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transcan 301 rhsImp Set to ‘"rand
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transcan 303 freq aty a vector of f
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transcan 305 categorical asis coef
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transcan 307 blood.pressure=60:260,
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translate 309 x[1:500]
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units 311 Value An object of class
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upData 313 The dataframeReduce func
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upData 315 fracmiss maxlevels minpr
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varclus 317 For valueTag
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varclus 319 df s similarity type me
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varclus 321 description, and naplot
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wtd.stats 323 Usage expand x by the
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wtd.stats 325 Author(s) Frank Harre
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xYplot 327 xYplot xyplot and dotplo
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xYplot 329 probs=c(.5,.25,.75), nx=
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xYplot 331 Details Value minor.tick
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xYplot 333 xYplot(Cbind(y,lower,upp
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yearDays 335 setTrellis() # blank c
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Index ∗Topic IO csv.get, 40 getZi
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INDEX 339 ∗Topic iplot labcurve,
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INDEX 341 (summary.formula), 266 [.
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INDEX 343 is.discrete (discrete), 6
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INDEX 345 print.dvi (latex), 142 pr
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INDEX 347 units
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