search for: prostate

In the package lasso2, there is a Prostate Data. To find coefficients in the prostate cancer example we could impose L1 constraint on the parameters. code is: data(Prostate) p.mean <- apply(Prostate, 5,mean) pros <- sweep(Prostate, 5, p.mean, "-") p.std <- apply(pros, 5, var) pros <- sweep(pros, 5, sqrt(p.st...

...the variable matrix. This is not worked out. Could anyone suggest where I am going wrong? I understand that I may not have the mean/intercept correct, but the scaling is also off, which suggests a bigger mistake. Thanks for your help. Juliet Hannah library(ElemStatLearn) library(glmnet) data(prostate) # training data data.train <- prostate[prostate$train,] y <- data.train$lpsa # isolate predictors data.train <- as.matrix(data.train[,-c(9,10)]) # test data data.test <- prostate[!prostate$train,] data.test <- as.matrix(data.test[,-c(9,10)]) # scale test data by using means an...

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...(C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i386-pc-mingw32/i386 (32-bit) # output truncated > options(chmhelp = FALSE, help_type = "text") > .help.ESS <- help > options(STERM='iESS', editor='gnuclient.exe') > load('prostate.sav') > library(rms) Loading required package: Hmisc Loading required package: survival Loading required package: splines Hmisc library by Frank E Harrell Jr Type library(help='Hmisc'), ?Overview, or ?Hmisc.Overview') to see overall documentation. NOTE:Hmisc no longer redefines...

Hi Everyone, I have a question regarding the construction of 3D graphs in 'R', BUT these graphs also need to illustrate movement (with time) of the prostate gland (using radiological techniques). I am not sure how to do this in 'R' although I'm sure there is some way of doing it. Below, I have copied and pasted some of the data with which I'm working on. The data are for axial images of the prostate for four patients (N1, N2, N3 a...

...ple for a package, I want to use data from another package, but avoid loading the entire package and avoid errors/warnings if that other package is not available. If I don't care about loading the other package, I can just do: if (require("ElemStatLearn", quietly=TRUE)) { data(prostate) # rest of example } I'd rather just be able to do something like: if (data(prostate, package="ElemStatLearn")) { # rest of example } but it appears that data() doesn't return anything useful (like FALSE or NULL) in case the named data set doesn't exist, or the pack...

Hi, First, when I try the example Prostate with bound 0.44 (as in the manual), I got a different result: > l1c.P <- l1ce(lpsa ~ ., Prostate, bound=0.44) > l1c.P .... Coefficients: (Intercept) lcavol lweight age lbph svi 1.0435803 0.4740831 0.1953156 0.0000000 0.0000000 0.3758199...

...\\Numbers after percents are frequencies.\\\indent Tests used:\\\textsuperscript{\normalfont 1}Wilcoxon test; \textsuperscript{\normalfont 2}Pearson test \end{table} ###Then I did another example from Harrell?s "statistical tables and plots...." rm(list=ls()) library(Hmisc) getHdata(prostate) # Variables in prostate had units in ( ) inside variable labels. Move # these units of measurements to separate units attributes # wt is an exception. It has ( ) in its label but this does not denote units # Also make hg have a legal R plotmath expression prostate<-upData(prostate, moveUnits=TR...

I have the following files list: > list.files() [1] "Prostate-Cancer_cvs_Dir" [2] "Prostate_Cancer-miRNAs&Genes.Pathway.xml" [3] "Prostate_Cancer_Pathways-miRNAs-GeneTargets-Dir" [4] "Prostate_Cancer_Pathways-miRNAs-GeneTargets-Dir.zip" [5] "Prostate-miRNAs.OrganTargets...

Hi, I need to build ROC curve in R, can you please provide data steps / code or guide me through it. Thanks and Regards Rithesh M Mohan [[alternative HTML version deleted]]

...: 'Design' The following object(s) are masked from package:survival : Surv, survfit The following object(s) are masked from package:Hmisc : .R., .SV4. Warning message: package 'Design' was built under R version 2.7.2 > prostate NOTE THAT DATA SET prostate exists patno stage rx dtime status age wt pf hx sbp dbp ekg hg sz 1 1 3 0.2 mg estrogen 72 alive 75 76 normal activi...

...an 14 CNS:SF_295 -3.09348 -1.00095 CNS 54 OV:OVCAR_4 -3.13137 -0.47497 Ovarian 36 LE:HL_60 -3.16745 -3.16745 Leukemia 38 LE:MOLT_4 -3.20055 -1.72841 Leukemia 11 BR:MDA_MB_231 -3.24907 1.58326 Breast 59 PR:PC_3 -3.36612 1.39328 Prostate 19 CO:HCT_116 -3.39764 0.43061 Colon 12 BR:T47D -3.41228 1.13818 Breast 22 CO:HCT_15 -3.45342 0.16357 Colon 64 RE:RXF_393 -3.49615 2.59144 Renal 28 LC:HOP_62 -3.4968 0.67884 Lung 60 RE:786_0 -3.5086 1.75056...

...reading Frank Harrell's wonderful Regression Modeling Strategies book and ran into a problem following the example in Chapter 8. I'm working on platform: Ubuntu 8.04 (i486-pc-linux-gnu) R version: 2.7.2 (2008-08-25) and my command sequence was: library(chron) library(Hmisc) load("prostate.sav") describe(prostate) The last command returned the error message: Error in formatDateTime(dd, atx, !timeUsed) : could not find function "format.dates" Thanks for any help you can give. Bob

...multiple positions in and around bioinformatics, biostatistics and computational biology. These range from HPC and mathematical programming, through biostatistics and biomarkers, to computational biology and bioinformatics. Focuses include single cell genomics and personalised medicine in lung and prostate cancer. For full details, please visit our website at: http://www.cruk.manchester.ac.uk Brief summaries below: RNA Biology Group - Crispin Miller ========================== Postdoctoral Scientist in Computational Biology: A position is now available for a highly motivated postdoctoral research...

...1 6.019 9.384 36 Melanoma 1 2.711 9.801 37 Melanoma 1 6.570 10.049 38 Melanoma 3 7.838 11.364 39 Ovarian 1 9.067 11.060 40 Ovarian 1 8.645 11.849 41 Ovarian 3 7.079 10.937 42 Ovarian 3 9.626 11.911 43 Ovarian 3 8.478 10.954 44 Ovarian 3 8.890 12.076 45 Prostate 3 8.356 12.486 46 Prostate 3 9.074 11.841 47 Renal 3 9.117 12.324 48 Renal 3 9.522 12.362 49 Renal 3 9.487 12.030 50 Renal 3 8.322 12.798 51 Renal 3 9.359 12.714 52 Renal 3 11.611 13.344 53 Renal 3 9.663 12.004 54 Renal 3 9.819 13.214...

...into R. The program perform cross validation as it stated. #1. Randomly divide the data set into 10 sets of equal size, ensuring equal numbers of events in each set #2. Fit the model leaving out the 1st set #3. Apply the fitted model in (2) to the 1st set to obtain the predicted probability of a prostate cancer diagnosis. #4. Repeat steps (2) to (3) leaving out and then applying the fitted model to the ith group, i = 2, 3... 10. Every subject now has a predicted probability of a prostate cancer diagnosis. #5. Using the predicted probabilities, compute the net benefit at various threshold probabilit...

Sir, I found your description of the dataset about nodal involvement in prostate cancer. It comes from the book biostatistics casebook. I like to use the dataset for doing logistics regression. Can you tell me where I can find the dataset. Thanks and greetings Wim van Baarle wvbaarle@wxs.nl [[alternative HTML version deleted]]

...Mean_expression A 3 0.25 Is there an easy way to do this using "cast" or "melt"? Ideally, I would also like to see the unique probes corresponding to each gene in the wide format. Thanks in advance Max Maxy Mariasegaram| Reserach Fellow | Australian Prostate Cancer Research Centre| Level 1, Building 33 | Princess Alexandra Hospital | 199 Ipswich Road, Brisbane QLD 4102 Australia | t: 07 3176 3073| f: 07 3176 7440 | e: mariaseg@qut.edu.au [[alternative HTML version deleted]]

Dear Rexperts, I am trying to add a '+' identifying the mean in a boxplot using the following sizelist <- split(size, grp) centers <- boxplot(sizelist, style.bxp = "att", medpch = "o", ylab = "Prostate Volume (cm3)") points(centers, unlist(lapply(sizelist, mean)), pch = "+") But, I get error Error in xy.coords(x, y) : 'x' and 'y' lengths differ which I do not understand. The data follows grp size AE 9.132 AE 10.07 AE 20.077...

Dear R users, I am a new R user and something stops me when I try to write a academic article. I want to make a nomogram to predict the risk of prostate cancer (PCa) using several factors which have been selected from the Logistic regression run under the SPSS. Always, a calibration plot is needed to validate the prediction accuracy of the nomogram. However, I tried many times and read a lot of posts with respect to this topic but I still couldn...