search for: placebo

I have an outlier that I would still like to display, but would prefer to shorten the axis. For example, display 0% - 40%, and 90% - 100%. Is this possible? I am using an xyplot. Thanks Murray -- Murray Pung Statistician, Datapharm Australia Pty Ltd 0404 273 283 [[alternative HTML version deleted]]

...(df)[2]) stop("Too many var.names given.") else names(df) <- var.names } df } __end__ expand.table.R Thus for the following table library(vcd) art <- xtabs(~Treatment + Improved, data = Arthritis) > art Improved Treatment None Some Marked Placebo 29 7 7 Treated 13 7 21 expand.table (above) gives a data frame of sum(art)=84 observations, with factors Treatment and Improved. > artdf <- expand.table(art) > str(artdf) 'data.frame': 84 obs. of 2 variables: $ Treatment: Factor w/ 2 levels "Plac...

...glmnet for variable selection and then generate a Cox regression) - That is, if I get an HR of 3 for the variable 300mg what does it mean ? the hazard is 3 times higher of what ? Here is some code to reproduce the issue: # Create a 4 level example factor trt <- factor( sample( c("PLACEBO", "300 MG", "600 MG", "1200 MG"), 100, replace=TRUE ) ) # Use contrasts to get the identity matrix of dummy variables to be used in glmnet trt2 <- contrasts (trt,contrasts=FALSE) Results (as you can see all levels are represe...

Hallo! I have two groups (placebo/verum), every subject is measured at 5 times, the first time t0 is the baseline measurement, t1 to t4 are the measurements after applying the medication (placebo or verum). The question is, if there is a significant difference in the two groups and how large the differnce is (95% confidence interva...

...t and now really need some help in the model below: Fit=gam(y~treat+SEQUENCE+PERIOD+SEX+s(x),data=dat, random=list(SUBJID=~1),correlation=corAR1(form=~1|SUBJID)) And error message keeps coming out when I want to compare the differences between treatments: Diff=contrast(Fit, list(treat=treatment[-placebo.pos]),list(treat="Placebo"), conf.int=0.9)-- (here placebo.pos=position of "Placebo" in treatment vector) I wonder if the function contrast could be used here? If not, what other options I might have? I hope it's not a stupid question… Thanks a lot! Xia Li [[alternativ...

Dear R-users, In a randomized placebo-controlled within-subject design, subjects recieved a psycho-active drug and placebo. Subjects filled out a questionnaire containing 15 scales on four different time points after drug administration. In order to detect drug effects on each time point, I compared scale values between placebo and dru...

...lustrate my question below using an example from the book. Thank you. Keith > #### > library(Hmisc) > > set.seed(173) > sex = factor(sample(c("m", "f"), 500, rep = T)) > age = rnorm(500, 50, 5) > treatment = factor(sample(c("Drug", "Placebo"), 500, rep = T)) > summary(sex ~ treatment, fun = table) sex N=500 +---------+-------+---+---+---+ | | |N |f |m | +---------+-------+---+---+---+ |treatment|Drug |263|140|123| | |Placebo|237|133|104| +---------+-------+---+---+---+ |Overall | |500|273...

...o achieve a couple of things, both of which are fully illustrated in self-contained code (and mostly minimal, although that left quite a bit) following this written description. 1. I quite often like to use a 'ghosted' reference across facets - for example, in my example program below, the placebo quartiles and median are reflected into each of the dose groups to facilitate easier cross referencing. Note that this reflection is done per-row. Is there a simple way of doing this in ggplot2 without having to create an artificial data set to fool it? 2. Some of my clients like their x-axes (in...

...e a data frame I would like the bottoms of them padded with NAs, without explicitly specifying that. When I do: anxiety.data = data.frame(Behavior_Therapy = c(6, 7, 6, 5, 5, 5, 7, 8, 9, 6, 6, 7), Atenolol = c(4, 8, 10, 3, 6, 5, 6, 3, 7, 5, 4, 6), Placebo = c(0, 7, 0, 7, 0, 7)) It duplicates the values for Placebo twice. I can correct this by doing: anxiety.data = data.frame(Behavior_Therapy = c(6, 7, 6, 5, 5, 5, 7, 8, 9, 6, 6, 7), Atenolol = c(4, 8, 10, 3, 6, 5, 6, 3, 7, 5, 4, 6), Placebo = c(c(...

...0.159 0.853 0.168 -0.947 0.34 Likelihood ratio test=0.91 on 2 df, p=0.635 n= 294 > glht(fit,linfct=mcp(treatment='Tukey')) General Linear Hypotheses Multiple Comparisons of Means: Tukey Contrasts Linear Hypotheses: Estimate pyridoxine - placebo == 0 -0.06303 thiotepa - placebo == 0 -0.15885 thiotepa - pyridoxine == 0 -0.09582 However, once I added a strata term in the formula of coxph(), then glht() can't work anymore: > (fit<-coxph(Surv(stop, status>0)~treatment+strata(enum),bladder1)) coxph(formula = Surv(stop, statu...

Dear all, I am trying to create a list, where each list element is a vector of different length arrays that contain 2by2 matrices. To be more specific there are 11 treatments that are compared with placebo (we have 11 comparisons) and each comparison is studied by a different number of trials and each trial has a different number of missing participants in both arms. The length of the list is equal to the number of comparisons. In each comparison the number of arrays is equal to the number of trials...

...ice. Thanks, --Matt Matt Austin Statistician, Amgen Inc. Example of problem derived from example(layout) code. ##Start windows() x <- pmin(3, pmax(-3, rbeta(5000,1,5))) y <- pmin(3, pmax(-3, c(rnorm(2500, .25, 1), rnorm(2500))) ) trtp.f <- factor(rep(c("Placebo", "Not Placebo"), each=2500), levels=c("Placebo", "Not Placebo")) xdens <- tapply(x, trtp.f, density, na.rm=TRUE) ydens <- tapply(y, trtp.f, density, na.rm=TRUE) topx <- max(unlist(lapply(xdens, function(x) max(x$y)))) topy <- max(unlist(...

It was recently pointed out on the lists that the S-PLUS Trellis suite has a function called reorder.factor that's useful in getting useful ordering of factors for graphs. I happily went ahead and implemented it, but it turns out that R (not S-PLUS) has a generic called reorder (with a method for "dendrogram"). Naturally, this causes R to think I'm defining a method for

Hi all, I am trying to parse a vector for caliculating minimum in that vector the vector having values like 1 Kontrolle 2 Placebo 3 125mg/kg 4 250mg/kg 5 500mg/kg 6 1000mg/kg hear i tries for comverting it into numeric with using "as.numaric()" function but i got values like 5 6 2 3 4 1 it gives 1000mg/kg is the least one but i have toget 125mg/kg as the minimum value for that i hav...

...D"), each = 18)) ) ## this plot correctly provides the key for the grouping color xyplot(Y ~ X, data=dat, type="p", panel=panel.superpose, groups=Drug, col = rep(c("red", "black"), 18), auto.key = list(space = "top", text = c( "Placebo", "Drug"), points = FALSE, lines = TRUE), par.settings = list(superpose.line = list(col = c("red","black") ) ) ) ## this plot correctly uses ID's and colors instead of plotting symbols xyplot(Y ~ X, data=dat, type="n", lab = dat$ID,...

...r the question is very stupid. In the past I had asked this before, and never got a reply (in other cases, the response was within hours). I also checked the S-list, where several similar enquiries of other people are orphaned. We have a cross-over design, where patient are treated two weeks with placebo, two weeks with a drug ("verum"), and a washout phase in between. For each phase, there is ONE number (let's call it "glucose level") describing the treatment effect. Blind treatement sequence is Seq=1 for placebo/verum, Seq=2 for verum/placebo. In Pinheiro/Bates, cross-ove...

...atients where there is also a treatment factor called "drug". Time is treated as categorical. What code is necessary to test for a treatment effect at a single time point, e.g., time = 3? Does the answer matter if the design is a crossover design, i.e, each patient received drug and placebo? Finally, what would be a good response to someone that suggests to do a simple t-test (paired in crossover case) instead of the test above within a mixed model? thanks! dave z = rnorm(24, mean=0, sd=1) time = rep(1:6, 4) Patient = rep(1:4, each = 6) drug = factor(rep(c("I", "P&...

...nd continuous variables? I would prefer to show 35 (10%) and 1.5 (1.2-1.8) rather than 10% (35) and 1.2 / 1.5 / 1.8. Here is a simple example: sex <- factor(sample(c("m","f"), 500, rep=TRUE)) age <- rnorm(500, 50, 5) treatment <- factor(sample(c("Drug","Placebo"), 500, rep=TRUE)) s1 <- summary(~sex + age) s2 <- summary(treatment ~ sex + age, method="reverse") print(s1); print(s2) Descriptive Statistics (N=500) +-------+-----------------+ | | | +-------+-----------------+ |sex : m| 46% (232) | +-------+-...

...e | Marked | Total -----------------+------------+--------+--------+-------------+ Active | Female | 6 | 5 | 16 | 27 | Male | 7 | 2 | 5 | 14 ----------------+-------------+--------+--------+-------------+ Placebo | Female | 19 | 7 | 6 | 32 | Male | 10 | 0 | 1 | 11 ---------------+-------------+---------+--------+-------------+ Total 42 14 28 84 if i do: y<- matrix(c(5,6,1...

...rest (once I adjusted the numerics to characters), it's just failing on the greek characters. Any suggestions welcomed. Jim Price. Cardiome Pharma Corp. Test code: plot(1:5, type = 'n') # The not bold version text(2, 2:4, cex = 2, labels = do.call(expression, unlist(list('Placebo', lapply(c(3, 6), function(.x) substitute(.x ~~ mu * g / kg / hr, list(.x = .x)))), recur = F))) # The bold version - note that the greek letter doesn't change text(4, 2:4, cex = 2, labels = do.call(expression, unlist(list(substitute(bold(Placebo)), lapply(as.character(c(3, 6)), functio...