search for: dose

Hey, everyone, I am using proportional odds model for ordinal responses in dose-response experiments. For some samll data, SAS can successfully provide estimators of the parameters, but the built-in function polr() in R fails. Would you like to tell me how to make some change so I can use polr() to obtain the estimators? Or anyone can give me a hint about the conditions for t...

...tract those labels into titles for plots generated from component objects. If someone could set me straight, I would appreciate it. For your amusement, I have provided an example of the Byzantine code I am currently using to avoid loops: # Simulate ANOVA type test data sex<-c(rep(1,8),rep(0,8)) dose<-c(rep(1,4),rep(0,4)) treatment<-c(rep(1,2),rep(0,2)) fix<-sex+dose+treatment Response<-fix+rnorm(16) Sex<-rep("Male",16) Sex[sex==0]<-"Female" Dose<-rep("High",16) Dose[dose==0]<-"Low" Treatment<-rep("A",16) Treatment[tre...

Dear All,   #I have the following code   Dose<-1000 Tinf <-0.5 INTERVAL <-8 TIME8 <-matrix(c((0*INTERVAL):(1*INTERVAL))) TIME7 <-matrix(c((0*INTERVAL):(2*INTERVAL))) TIME6 <-matrix(c((0*INTERVAL):(3*INTERVAL))) TIME5 <-matrix(c((0*INTERVAL):(4*INTERVAL))) TIME4 <-matrix(c((0*INTERVAL):(5*INTERVAL))) TIME3 <-matrix(c(...

Hi, ?I have a list of files in one of my working directories: "chr17.chunk1.dose.fvd" "chr17.chunk1.dose.fvi" "chr17.chunk1.prob.fvd"? "chr17.chunk1.prob.fvi"? ........... ......... ........ "chr17.chunk10.dose.fvd" "chr17.chunk10.dose.fvi" "chr17.chunk10.prob.fvd" "chr17.chunk10.prob.fvi"...

...oisson Regression) which is just too big for my modest understanding of stats!!! Here goes... I want to find good literature or proper mathematical procedure to calculate a confidence interval for an inverse prediction of a Poisson regression using R. I'm currently trying to analyse a "dose-response" experiment. I want to calculate the dose (X) for 50% inhibition of a biological response (Y). My "response" is a "count" data that fits a Poisson distribution perfectly. I could make my life easy and calculate: "dose response/control response" = % of...

Hi folks, Win7 64bit R 1.12.0 I run following command on R:- > ToothGrowth > attach(ToothGrowth) > plot(dose,len) > matrics=lm(len~dose) > abline(metrics) Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : plot.new has not been called yet Only a grey diagram is displayed without content > plot(abline(metrics)) Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, .....

All, I am constructing a pharmacokinetic dataset and have hit a snag. The dataset can be demonstrated in the following way: myData <- data.frame( evid = c(1, 0, 0, 0, 1, 0, 1, 1, 1, 0), time = 1:10, last.dose.time = c(1, 1, 1, 1, 5, 5, 7, 8, 9, 9) ) The evid field is an indicator variable for whether the associated observation is a dosing record (when it takes value 1) or an observation (where it takes value 0). The time field is a date-time record for the associated dose / observation event. I'm...

Dear list, This may sound silly. What is the right way to change the names of a dataframe? Let's say I have this data frame (dose) with four columns with names "ID", "DOSE", "TIME" "CMT". I want to change "DOSE" to "AMT". So I did names(dose[2])<-'AMT' But nothing happened. The name of the second column is still "DOSE". Only this works names(...

...y other efficient way deal with. The following is my code. I am ready to provide any other description of my function if you need to move forward. ------------------------------------------------------------------------------------------------------------------------------------ library(cubature) dose<-c(2,3,5) y0<-c(2,1,0) y1<-c(1,1,1) y2<-c(0,1,2) lf<-function (x) { v<-1 for (i in 1:length(dose)) { psi0<-1/((1+exp(x[1]+x[2]*dose[i]))*(1+exp(x[3]+x[4]*dose[i]))) psi1<-exp(x[1]+x[2]*dose[i])/((1+exp(x[1]+x[2]*dose[i]))*(1+exp(x[3]+x[4]*dose[i])))...

...a relationship with the kill rate of rats. But i cant seem to work it out as i have two predictor variables~help?Thanks.:) Here's my data. > rat.toxic<-read.table(file="Rats.csv",header=T,row.names=NULL,sep=",") > attach(rat.toxic) > names(rat.toxic) [1] "Dose" "Sex" "Dead" "Alive" > rat.toxic Dose Sex Dead Alive 1 10 F 1 19 2 10 M 0 20 3 20 F 4 16 4 20 M 4 16 5 30 F 9 11 6 30 M 8 12 7 40 F 13 7 8 40 M 13 7 9 50 F 18...

...ents and questionnaires" http://cran.r-project.org/doc/contrib/rpsych.htm they describe a balanced data set for a drug experiment: "... a test of drug treatment effect by one between-subject factor: group (two groups of 8 subjects each) and two within-subject factors: drug (2 levels) and dose (3 levels). " This design is identical to an unbalanced one that I am interested in analyzing in R. I have both missing cells and unequal number of observations per cell. This is a repeated-measures design with test subject as a random factor. Baron and Li show how to analyze this design usi...

...a; de lo contrario, todo fallara. Tengo algunas lineas que mitigan un poco el problema, pero no cuando hay problemas de convergencia como el que se ilustra a continuacion: # datos d <- structure(list(y = c(509.75, 498.8629, 584.9069, 808.5421, 679.3904, 597.3327, 561.4653, 496.4428, 474.4776), dose = c(2.27726728500976, 1.65500383670491, 2.93012117741345, 7.29822890763926, 7.77257337407207, 8.42489485944128, 9.1495092419634, 12.1197337185771, 11.7126676116462 )), .Names = c("y", "dose"), row.names = c(NA, -9L), class = "data.frame") # curva # install.packages(...

Dear all, I can use the very nice drc package (multdrc()) to model and plot a dataframe containing dose and response values. I can also use predict.drc() to yield response values given a dose. I need to do the opposite, estimate a dose given the response. The general predict documentation seems to say that this is possible, but it does not appear that predict.drc has that capability. This mak...

I have a dataset with event=death time (from medical examination until death/censoring) dose (given at examination time) Two groups are considered, a non-exposed group (dose=0), an exposed group (dose between 5 and 60). For some reason there is a theory of the dose increasing its effect over time (however it was only given (and measured) once = at the time of examination). I tested a...

Hello, I used the glm function in R to fit a dose-response relationship and then have been using dose.p to calculate the LC50, however I would like to calculate the NOEL (no observed effect level), ie the lowest dose above which responses start occurring. Does anyone know how to do this? [[alternative HTML version deleted]]

Hi, I have a data set in which the variable 'dose' is time-varying. Currently, the data set is in a long format, with 1 row for each time unit of follow-up for each individual "Id". It looks like this: orig.data <- cbind(Id = c(rep(1,4), rep(2,5)), time = c(1:4, 1:5), dose = c(1,1,1,0,1,0,1,1,0)) orig.data Id time dose [...

I'm analysing some ID50 data for 2 different groups and had already calculated this by hand using Reed-Muench formula, when I came across the dose.p function in R. I have 2 queries: 1) dose.p gives me a different answer to Reed-Muench, and actually I suspect wrong answer, given that the dose.p result dosage stated to infect 50% is actually stronger than the dose used in my experiments caused above 50% infection! >SetA<-data.frame(c(&...

Dear all I need to obtain an estimate of the 50% lethal dose (LD50) from a logistic regression model obtained by applying the glm procedure to some binomial data. The model appears to fit the data very well. I used dope.p from MASS to try and find LD50. The following output appears: > dose.p(iso.glm.logit, cf = c(1,3), p = 1:3/4) Error in dose.p(iso....

...7 4 Heard 151 157 60 82 5 6 ... As I see it thats a summary of data from several published trials. What I want to do is do a forrest (forest) plot for subgroups within my single dataset as a test of heterogeniety. I have a dataset who received either full dose(FD) or reduced dose(RD) treatment, and a number of characteristics about those subjects: age, sex, renal function, weight, toxicity. And I have survival data (censored). they are in standard columnar data. Is there an *easy* way to transform them into something like this: SubGroup...

Dear R-user, I'm having some difficulty with working PFIM 3.2, a package for implementing population PK/PD in R. I wish to evaluate the determinant of Fisher information matrix each time with successive dose from a pre defined sequence of doses and want to store those values in a vector. It's important to note that in my 'stdin.r' file, dose<-c(u) and each time u is to be replaced as I said. I think a quick look on the following R codes will give a more clearer picture of the objective:...