search for: logdose

...or not in their responses to insecticide. My problem is that I have up to four replicates for some genotypes, but only one for other... Due to this unbalanced design, I thought of using lmer procedure (lme4). Here are the data, the model and the R output: > dataf geno ml bouteille dose logdose tot mort date 1 D1D1 0.4 0.10 4e-04 -3.397940 32 0 1 2 D1D1 0.4 0.10 4e-04 -3.397940 83 4 2 3 D1D1 0.5 0.10 5e-04 -3.301030 120 17 2 4 D1D1 0.5 0.10 5e-04 -3.301030 114 2 4 5 D1D1 0.6 0.10 6e-04 -3.221849 34 10 1 6 D1D1 0.6 0....

Dear R-list, I have a data set from 20 pigs, each of which is tested at crossed 9 doses (logdose -4:4) and 3 skin treatment substances when exposed to a standard polluted environment. So there are 27 patches on each pig. The response is irritation=yes/no. I want to determine "equally effective 50% doses" (similar to old LD50), and to test the treatments against each other. I am look...

termplot() does not carry subsetting over to carriers that are in the environment but not in the data frame. This generates a "subscript out of bounds" error. > data(ToothGrowth) > logdose <- log(ToothGrowth$dose) > tooth.lm <- lm(len ~ logdose, data=ToothGrowth) > termplot(tooth.lm) ## Works fine > toothVC2.lm <- lm(len ~ poly(dose,2), data=ToothGrowth, + subset=ToothGrowth$supp=="VC") > termplot(toothVC2.lm) ## Works fine &...

Hi, I have recently been attempting to find the LD50 from two predicted fits (For male and females) in a Generalised linear model which models the effect of both sex + logdose (and sex*logdose interaction) on proportion survival (formula = y ~ ldose * sex, family = "binomial", data = dat (y is the survival data)). I can obtain the LD50 for females using the dose.p() command in the MASS library with dose.p(mod1,c(1,2)). However I cannot find a way to determine t...

...6.832, 11.118, 1.319, 5.495, -3.352, 102.464, 83.114, 50.631, 22.792, 18.348, 19.066, 27.794, 14.682, 11.992, 12.868)) m<- drm(response ~ (log10(dose*1e6)), data = d, fct = l4(fixed = c(NA,NA,NA,NA), names = c("hs", "bottom", "top", "ec50")), logDose = 10, control = drmc(useD = T)) summary(m) results in: Model fitted: Log-logistic (ED50 as parameter) (4 parms) Parameter estimates: Estimate Std. Error t-value p-value hs:(Intercept) -9.8065e-01 2.5821e-03 -3.7979e+02 2.248e-33 bottom:(Intercept) 1.0955e+01 2...

...ng curve and IC50. My 384 well format raw data contains multi dose response curves. My script goes through set of data then produce curve and ic50. Here is my sudo code: For (plateid in platelist) { Input data (plateid) as matrix Curve fitting model4logistic <- multdrc(rdata ~ ld, logDose=10) } The first 3 plates are ok, 4th plate has following error Error in mdrcOpt(opfct, startVec, optMethod, derFlag, constrained, warnVal, : Convergence failed I know the expected fitting is ugly, is it the reason to produce the error? Thanks you in advance for your help, X...

...r message: can anybody suggest how to deal with this? Error in if (ratio0[i] < log(runif(1))) { : missing value where TRUE/FALSE needed ################### original program ######## p2 <- function (Nsim=1000){ x<- c(0.301,0,-0.301,-0.602,-0.903,-1.208, -1.309,-1.807,-2.108,-2.71) # logdose n<-c(19,20,19,21,19,20,16,19,40,81) # total subject in dose-response experiment y<-c(19,18,19,14,15,4,0,0,0,2) # success in each trials dta<-cbind(x,n,y) dta<-as.data.frame(dta) # creating data frame proposal.b0 = current.b0 = ratio0 = double(Nsim) # blank vector proposal.b1 = current....