search

harrelfe / rms

Regression Modeling Strategies
https://hbiostat.org/R/rms
Other
170 stars 48 forks source link

After plot with nomogram(), the outputs are crowded together and the lines don't strehch #114

Closed BloomingFlowers closed 2 years ago

BloomingFlowers commented 2 years ago

I've finished the plot with the code below. library(survival) library(rms) riskFile="train.txt" risk2=read.table(riskFile, header=T, sep="\t", check.names=F, row.names=1) dd <- datadist(risk2) options(datadist="dd") f2 <- lrm(VTE ~ age+duration+ALB+DD+R012, data=risk2, x=T,y=T) nom <- nomogram(f2, fun=plogis,lp=F, funlabel = "Risk") plot(nom)

and the result is ugly and strange as the pic shows image

How could I draw a longer and better line?

Relly appreciate your help!

here print the dput() nom <- structure(list(age = structure(list(age = c(25L, 30L, 35L, 40L, 45L, 50L, 55L, 60L, 65L, 70L, 75L, 80L), Xbeta = c(1= 4.14584218573903, 2= 4.97501062288683,3= 5.80417906003464,4= 6.63334749718244, 5= 7.46251593433025,6= 8.29168437147805,7= 9.12085280862586, 8= 9.95002124577366,9= 10.7791896829215,10= 11.6083581200693, 11= 12.4375265572171,12= 13.2666949943649), points = c(1= 0, 2= 9.09090909090909,3= 18.1818181818182,4= 27.2727272727273, 5= 36.3636363636364,6= 45.4545454545455,7= 54.5454545454545, 8= 63.6363636363636,9= 72.7272727272727,10= 81.8181818181818, 11= 90.9090909090909,12= 100)), info = list(nfun = 1, predictor = "age", effect.name = "age", type = "main")), duration = structure(list(duration = 8:18, Xbeta = c(13= 4.86268437212434, 14= 5.47051991863988,15= 6.07835546515542,16= 6.68619101167096, 17= 7.2940265581865,18= 7.90186210470205,19= 8.50969765121759, 20= 9.11753319773313,21= 9.72536874424867,22= 10.3332042907642, 23= 10.9410398372798), points = c(13= 0,14= 6.66424027740798, 15= 13.328480554816,16= 19.992720832224,17= 26.6569611096319, 18= 33.3212013870399,19= 39.9854416644479,20= 46.6496819418559, 21= 53.3139222192639,22= 59.9781624966719,23= 66.6424027740799 )), info = list(nfun = 1, predictor = "duration", effect.name = "duration", type = "main")), ALB = structure(list(ALB = c(20L, 25L, 30L, 35L, 40L, 45L, 50L, 55L, 60L, 65L), Xbeta = c(24= -3.35961351152051, 25= -4.19951688940064,26= -5.03942026728077,27= -5.8793236451609, 28= -6.71922702304102,29= -7.55913040092115,30= -8.39903377880128, 31= -9.23893715668141,32= -10.0788405345615,33= -10.9187439124417 ), points = c(24= 82.8774519173499,25= 73.6688461487554, 26= 64.460240380161,27= 55.2516346115666,28= 46.0430288429721, 29= 36.8344230743777,30= 27.6258173057833,31= 18.4172115371889, 32= 9.20860576859442,33= 0)), info = list(nfun = 1, predictor = "ALB", effect.name = "ALB", type = "main")), DD = structure(list(DD = c(0, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4), Xbeta = c(34= 0,35= 0.671520724233163,36= 1.34304144846633, 37= 2.01456217269949,38= 2.68608289693265,39= 3.35760362116581, 40= 4.02912434539898,41= 4.70064506963214,42= 5.3721657938653 ), points = c(34= 0,35= 7.36247737270889,36= 14.7249547454178, 37= 22.0874321181267,38= 29.4499094908356,39= 36.8123868635445, 40= 44.1748642362534,41= 51.5373416089623,42= 58.8998189816712 )), info = list(nfun = 1, predictor = "DD", effect.name = "DD", type = "main")), R012 = structure(list(R012 = 0:1, Xbeta = c(43= 0, 44= 2.20394845438508), points = c(43= 0,44= 24.163841919483 )), info = list(nfun = 1, predictor = "R012", effect.name = "R012", type = "main")), total.points = list(x = c(0, 20, 40, 60, 80, 100, 120, 140, 160, 180, 200, 220, 240, 260, 280)), Risk = list(x = c(153.468086161901, 162.359045411956, 168.268585249665, 173.112718166126, 177.558280786434, 182.003843406743, 186.847976323204, 192.757516160913, 201.648475410968), x.real = c(0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9), fat = c("0.1", "0.2", "0.3", "0.4", "0.5", "0.6", "0.7", "0.8", "0.9"), which = c(FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE ))), info = list(fun = list(function (q, location = 0, scale = 1, lower.tail = TRUE, log.p = FALSE) .Call(C_plogis, q, location, scale, lower.tail, log.p)), lp = FALSE, lp.at = c(-10, -8, -6, -4, -2, 0, 2, 4, 6, 8), discrete = c(age = FALSE, duration = FALSE, ALB = FALSE, DD = FALSE, R012 = TRUE), funlabel = "Risk", fun.at = NULL, fun.lp.at = NULL, Abbrev = list(), minlength = 4, conf.int = FALSE, R = structure(c(4.14584218573903, 13.2666949943649, 4.86268437212434, 10.9410398372798, -10.9187439124417, -3.35961351152051, 0, 5.3721657938653, 0, 2.20394845438508 ), dim = c(2L, 5L), dimnames = list(NULL, c("age", "duration", "ALB", "DD", "R012"))), sc = 10.9638870507182, maxscale = 100, Intercept = c(Intercept = -16.1948294400573), nint = 10, space.used = c(main = 5, ia = 0)), class = "nomogram") have a nice day

harrelfe commented 2 years ago

The RMS course notes have examples where plotting format is overridden for nomogram to solve this problem.