search for: ranef

The coxme package has a ranef() method, as does lme4. I'm having trouble getting them to play together, as shown below. (The particular model in the example isn't defensible, but uses a standard data set.) The problem is that most of the time only one of lme4 or coxme will be loaded, so each needs to define the basic...

I have been struggling all day to import a particular function/method combination (ranef(), which extracts the random effects from a mixed model fit) from the nlme package into another package ... so far without success. The NAMESPACE for nlme contains the following lines: export(..., ranef, ...) S3method(ranef, lme) ranef is defined as a standard S3 generic, function (object,...

Using ranef() (package nlme, version 3.1-75) with an 'lme' object I can obtain random effects for intercept and slope of a certain level (say: 1) - this corresponds to (say level 1) "residuals" in MLWin. Maybe I'm mistaken here, but the results are identical. However, if I try to get...

library(nlme) data(Phenobarb) na.include <- function(x)x phe1 <- nlme(conc~phenoModel(Subject, time, dose, lCl, lV), data = Phenobarb, fixed = lCl+lV~1, random= pdDiag(lCl+lV~1), start = c(-5,0), na.action = na.include, naPattern = ~!is.na(conc)) phe.ranef <- ranef(phe1,augFrame=TRUE) plot(phe.ranef, form=lCl~Wt+ApgarInd) [Error in max(length(x0), length(x1), length(y0), length(y1)) : Argument "x0" is missing, with no default] The cause is plain to see: in plot.ranef.lme we have staple.ends <- list(x1 = c(rep(X...

I'm testing out a new version of coxme and R CMD check fails with "could not find function ranef" (or random.effects or fixef, or anything from nlme). The NAMESPACE file has the line below importFrom(nlme, ranef, random.effects, fixef, fixed.effects, VarCorr) and nlme is declared in the DESCRIPTION file as an import. I feel that I must be staring at some obvious (but invisible to...

...times20) dat$Zt20 <- approx.Z(Zt20, times20, dat$time) fit1.20 <- lme(y~time, data=dat, random=list(all=pdIdent(~Zt20-1))) # Loess model dat.lo <- loess(y~time, data=dat) plot(dat.lo) # Spline model with(dat, lines(fitted(fit1.20)~time, col="red")) # Save random effects for later ranef.nlme <- unlist(ranef(fit1.20)) (2) Now an attempt to use lme4: library(lmeSplines) detach(package:nlme) library(lme4) data(smSplineEx1) # Use 20 spline in lme4 dat <- smSplineEx1 times20 <- seq(1,100,length=20) Zt20 <- smspline(times20) dat <- cbind(dat, approx.Z(Zt20, times20, dat...

User of the coxme library (mixed effects Cox models) are instructed to use ranef(), fixed(), VarCorr(), etc to retrieve bits out of a fitted model; it purposely uses the same methods as nlme and/or lmer. The current behavior is to "depend" on nlme. If I defined the methods myself in coxme, then someone who had both nlme and coxme loaded will suffer from "las...

...=list(y = "Height", x = "Time", units = list( y = "(m)", x = "(Yr)")) ) Warning message: argument lengths differ in: split(x, f). The warning did not affect the estimation of a nlme model with parameters B1, B2, and B3. However, when plotting the estimated ranef versus covariates, an error resulted > A1Mod.nlmeRE <- ranef(A1Mod.nlme, aug=T) > plot(A1Mod.nlmeRE, form = B1 ~ Ps + Dr + El + As + Sl) results in Error in max(length(x0), length(x1), length(y0), length(y1)) : Argument "x0" is missing, with no default The same data...

...nt" "n" "p" "q" ... ..@ fixef : num [1:2, 1:1000] 251.41 10.47 254.56 9.71 262.67 ... .. ..- attr(*, "dimnames")=List of 2 .. .. ..$ : chr [1:2] "(Intercept)" "Days" .. .. ..$ : NULL ..@ nc : int [1:2] 1 1 ..@ ranef : num [1:36, 1:1000] 1.51 -40.37 -39.18 24.52 22.91 ... ..@ sigma : num [1, 1:1000] 25.6 23.6 22.9 22.1 26.2 ... I assume that there is random effect samples for the intercept (1|Subject) and the slope (0+Days|Subject). The trouble is that I would like to get the samp0 at ranef for the...

Hi I'm getting the intercepts of the Random effects as 0. Please help me to understand why this is coming Zero This is my R code Data<- read.csv("C:/FE and RE.csv") Formula="Y~X2+X3+X4 + (1|State) + (0+X5|State)" fit=lmer(formula=Formula,data=Data) ranef(fit). My sample Data State Year Y X2 X3 X4 X5 X6 S2 1960 27.8 397.5 42.2 50.7 78.3 65.8 S1 1960 29.9 413.3 38.1 52 79.2 66.9 S2 1961 29.8 439.2 40.3 54 79.2 67.8 S1 1961 30.8 459.7 39.5 55.3 79.2 69.6 S2 1962 31.2 492.9 37.3 54.7 77.4 68.7 S1 1962 33.3 528.6 38.1 63.7 80.2 73.6 S2 1963 35.6 560.3...

...-lmer( x ~ (1|rtr)+ trth/(1|cs) , data=dtf) # Here, cs and rtr are crossed random effects. cs 1-5 are of type TRUE, cs 6-10 are of type FALSE, so cs is nested in trth, which is fixed. So for cs I should get a fit for 1-5 and 6-10. This appears to be the case from the random effects: > mean( ranef(mod1)$cs[[1]][1:5] ) [1] -2.498002e-16 > var( ranef(mod1)$cs[[1]][1:5] ) [1] 23.53083 > mean( ranef(mod1)$cs[[1]][6:10] ) [1] 2.706169e-16 > var( ranef(mod1)$cs[[1]][6:10] ) [1] 1.001065 However VarCorr(mod1) gives me only a single variance estimate for the cases. How do I get the othe...

...m up, I can't figure out how MLWin calculates the > standardized residuals. But I understand that this is not a > question for the R list. > Nevertheless, it would help if someone could point me to some > arguments why not to use them and stick to the results > obtainable by ranef(). Hi Dirk: Well, it is interesting that mlWin and lmer generate the same exact random effects but different results for the standardized random effects. Now, my prior post showed exactly how lme calculates the standardized random effects, so this is now totally transparent. What I would recomm...

...n-upwardly compatable change: Extractor functions: beta= fixed effects, b=random effects nlme lme4 coxme <2.2 coxme 2.2 lmekin 2.2 ------------------------------------------------------ beta fixef fixef fixef fixef fixef b ranef ranef ---- ranef ranef var(beta) vcov vcov ---- vcov vcov var(b) VarCorr VarCorr ranef VarCorr VarCorr Notice that "ranef" in the prior release was out of step with everyone else, which became obvious when working on...

...(NULL,c("Subject","Item","Response"))) for (s in c(1:23)) for (i in c(1:7)) b[7*(s-1)+i,] <- c(s,i,bb[s,i]) B <- data.frame(b) A.fit <- lmer(Response~(1|Subject)+(1|Item),A,binomial) B.fit <- lmer(Response~(1|Subject)+(1|Item),B,binomial) A.fit B.fit ranef(A.fit)$Item ranef(B.fit)$Item Generalized linear mixed model fit using Laplace Formula: Response ~ (1 | Subject) + (1 | Item) Data: A Family: binomial(logit link) AIC BIC logLik deviance 120 129 -56.8 114 Random effects: Groups Name Variance Std.Dev. Subject (Intercept) 1.63e+00...

...ra A y para B, pero al ser muchos y teniendo en cuenta el tiempo de procesamiento, donde el cálculo del modelo no sería necesario procesar por cada ejecución de variable (A y B). Expresado de otra forma, (1) es el procesamiento del modelo, (2.1) y (2.2) son procesos sobre el modelo, por ejemplo ranef para solo A y ranef para solo B. El resultado de ranef para A, es decir filtrando solo la vaiable A se escribe en el archivo A. Por lo que tendría dos archivos, uno A y otro B, donde ambos tienen una parte en común (1) y la correspondiente (2.1) para A y (2.2) para B. Mi deseo es no tener que...

On 16/02/2015 8:20 AM, Therneau, Terry M., Ph.D. wrote: > >> > I'm testing out a new version of coxme and R CMD check fails with "could not find function >> > ranef" (or random.effects or fixef, or anything from nlme). The NAMESPACE file has the >> > line below >> >> > importFrom(nlme, ranef, random.effects, fixef, fixed.effects, VarCorr) >> >> > and nlme is declared in the DESCRIPTION file as an impo...

>>>>> Therneau, Terry M , Ph D <therneau at mayo.edu> >>>>> on Sun, 15 Feb 2015 17:31:00 -0600 writes: > I'm testing out a new version of coxme and R CMD check fails with "could not find function > ranef" (or random.effects or fixef, or anything from nlme). The NAMESPACE file has the > line below > importFrom(nlme, ranef, random.effects, fixef, fixed.effects, VarCorr) > and nlme is declared in the DESCRIPTION file as an import. I feel that I must be staring >...

...sing lme. I want to use qqnorm and pairs (similarly to examples given in Pinheiro & Bates p. 188), but it's not working. Here's some relevant code and the error message: library(nlme) data(Machines) m1 <- lme(fixed=score~Machine,random=~1|Worker/Machine, data=Machines) qqnorm(m1, ~ranef(.)) Error in rep(names(fData), rep(nr, nc)) : invalid 'times' argument In addition: Warning message: In data.frame(Worker = list("(Intercept)" = c(-7.51429457896346, : row names were found from a short variable and have been discarded I also tried changing the last line to qq...

Hello. I'm running a generalized linear model and am interested in using the random effects that are output for further analysis. My random effect is interacting with two different fixed effects (which which are factors with two levels each). When I retrieve the random effects I get something like this: (Intercept) nutrient (Intercept) light (Intercept) Aa-0 0.59679192

...day | subjectno, data=Data1_93) detach(Data) Here is the code to check that the covariate called pcat is indeed a factor: > levels(pcat) [1] "1" "2" "3" > is.factor(pcat) [1] TRUE and then after the model is fitted I extract the random effects: D1C2.ran <- ranef(mod11.103nlme,augFrame=T) and here is an extract from the object: C R day gamedens pcat site mutcat1 pdens0 log2game NA02_259 -1.016987007 0.0162825099 15.75000 23.50000 1 Namaacha Mixed 15018 3.761099 NA02_073 -0.939355374 0.013258...