similar to: xyplot: filtering out empty plots

Hi all, Using xyplot I want to print to Y variables (y1, y2) versus X, conditional on the group. How can I obtain a line (type="l") for one relationship (ie. y1 ~ x) and points (type="p") for the other (y2 ~ x) ? library(lattice) # create some sample data df<-data.frame(group=as.factor(c(rep("a",4), rep("b",4))), # grouping variable for conditional

Hello, I have a data.frame with the following format: > head(clin2) Study Subject Type Obs Cycle Day Date Time 1 A001101 10108 ALB 44.00000 98 1 2004-03-11 14:26 2 A001101 10108 ALP 95.00000 98 1 2004-03-11 14:26 3 A001101 10108 ALT 61.00000 98 1 2004-03-11 14:26 5 A001101 10108 AST 33.00000 98 1 2004-03-11 14:26 I want to transform this

Hello, I am using Dr. Harrell's design package to make a nomogram. I was able to make a beautiful one without stratifying, however, I will need to stratify to meet PH assumptions. This is where I go wrong, but I'm not sure where. Non-Stratified Nomogram:

When I sink the output of an RWeka model to a text file, the output file appears empty: library(RWeka) model = LogitBoost(Species~.,data=iris) print(model) sink("output.txt") print(model) #file output.txt is created, but it is blank sink() Am I doing anything wrong? [[alternative HTML version deleted]]

>Hello, I am hoping for assistance in regards to examining the contribution of stratified variables in a cox regression. A previous post by Terry Therneau noted that "That is the point of a strata; you are declaring a variable to NOT be proportional hazards, and thus there is no single "hazard ratio" that describes it". Given this purpose of stratification, in the

Good afternoon! I'm trying to use the Survey package for a stratified sample which has 4 criteria on which the stratification is based. I would like to get the corrected weights and for every element i get a weight of 1 E.g: tipping design <- svydesign (id=~1, strata= ~regiune + size_loc + age_rec_hhh + size_hh, data= tabel) and then weights(design) gives

Hi, I’m new to R (just installed today) and I’m trying to figure out how to do stratified randomisation using it. My google search expedition has lead me to believe that blockrand package will most probably be the answer to it. I’ve played around with blockrand for awhile and tried the sample code: library(blockrand) ##stratified by sex male <- blockrand(n=100,

Hello all, I am trying to use xyplot to give a six panel plot and to highlight only points (in any panel) that meet a certain criterion. With the plot command I would do something like: plot.default(filein$Site,filein$circ.conc) points(filein$Site,filein$circ.conc,type="p", pch=ifelse(filein$p.value<5e-02,19,21)) I had thought I could just stick in the pch line from above into

In the example R script below, horizontal gray gridlines are drawn at y coordinates where the points are drawn with the code: panel.abline(h=y, v=xScale, col.line="gray") How do I change this so that the horizontal gray gridlines are drawn at y coordinates where the y labels are drawn? The challenge is that each panel has different y-ranges (in my real example the y-ranges and

I have a number of x, y observations (Time, Conc) for a number of Subjects (with subject number Subj) and Doses. I can plot the individual points with xyplot fine: xyplot(Conc ~ Time | Subj, Groups=Dose, data=myData, panel = function(x,y) { panel.xyplot(x, y) panel.superpose(???) # Needs more here } ) I also like to plot on

Hello, I would like to change the background color in only -one- of the strips in a multipanel lattice xyplot, from the default yellow-brown color. Until now, I only managed to change the background strip color in all of the strips using the par.settings, but I do not get it to work for only 1 strip. Below is the current code I am using. The resulting plot is here:

This should be simple but I am struggling. I like to easily switch in xyplot between a linear or logarithmic y-axis by setting a logical flag logY to False or True. This switch changes the scales argument of xyplot. I found out that the original two-dimentional data (Conc vs Time in my case) are converted to log10(Conc) if log=TRUE in scales, but it appears that functions like panel.curve need to

Hi all; I'm trying to display a 2 panel plot for the Puromycin data from R with 2 different non-linear models fitted to each group. The problem is that as far as I know panel.number doesn't work in the latest version of R. Can anyone give a hint how to solve this? Here is the code that I used before and now doesn't work xyplot(rate ~conc| state,Puromycin,

Hello everyone, I am trying to solve 2D differential equations using finite difference scheme in R. I have been able to work with the equations with only one spatial dimensions but I want to extend it to the two dimensional problem. For example i can simulate one dimensional diffusion using a code like the following. But I want to write a similar code for,say, a two dimensional diffusion

Hi all R users, I have problems with my second loop for drawing the three curves in the same graphic. I need help please Thank you in advance ######################################################################### simulation <- function(k, n){ conc <- seq(0,100,by=0.5) #choixg <- seq(1, length(conc)) choixg <- rep(0,length(conc)) for (i in 1:length(conc)){ choixg[i] <- (k

Hello all R users, My simulation function works correctly, but I have problems with plot function. You will find the following code using it. Thank you for your help ##################################################" simulation <- function(k, n){ conc <- seq(0,10,by=0.5) #choixg <- seq(1, length(conc)) choixg <- rep(0,length(conc)) for (i in 1:length(conc)){ choixg[i]

#how do I break these up into first two letters (RM), number, and then the last part #is there an easily accessible regex tutorial on the internet? v = (structure(1:122, .Label = c("RM215Temp", "RM215SpCond", "RM215DO.Conc", "RM215Depth", "RM215pH", "RM215ORP", "RM215Turbidity.", "RM215Battery", "RM215DO.",

Hi, I think you're misunderstanding which set of variables go on either side of the formula. Is this what you're looking for? > aggregate(OD ~ Time + Target + Conc, data = df, FUN = "mean") Time Target Conc OD 1 1 BACT 1 765.3333 2 1 BACT 2 745.3333 3 1 BACT 3 675.0000 > aggregate(ODnorm ~ Time + Target + Conc, data = df, FUN =

Hallo Everybody How do you specify arguments for a function used within another function? Here is my problem: I am reconstructing a calculator for the burden of disease due to air pollution from publications and tools published by the WHO. The calculations make use of published dose-response relationships for particular health end-points. This is then applied to populations with known or

Also, > aggregate(cbind(OD, ODnorm) ~ Time + Target + Conc, data = df, FUN = "mean") Time Target Conc OD ODnorm 1 1 BACT 1 765.3333 108.33333 2 1 BACT 2 745.3333 88.33333 3 1 BACT 3 675.0000 18.00000 (You might wish for "cbind(OD,ODnorm) ~ . - Well", but aggregate.formula is not smart enough for that.) -pd > On 24 Oct 2023, at