search for: lmercontrol

...her column. I used the code below to run my model using lmer. However, I get the following error. Please let me know how I can solve this error. Please note that I have 50% missing data in SA at age 12. modelLSI_maineff_RE <- lmer(SA ~ Index1* LSI+ (1 + Index1+LSI |ID), data = LSIDATA, control = lmerControl(optimizer ="bobyqa"), REML=TRUE) summary(modelLSI_maineff_RE) Error: number of observations (=1080) <= number of random effects (=1479) for term (1 + Index1 + LSI | ID); the random-effects parameters and the residual variance (or scale parameter) are probably unidentifiable I did test...

...her column. I used the code below to run my model using lmer. However, I get the following error. Please let me know how I can solve this error. Please note that I have 50% missing data in SA at age 12. modelLSI_maineff_RE <- lmer(SA ~ Index1* LSI+ (1 + Index1+LSI |ID), data = LSIDATA, control = lmerControl(optimizer ="bobyqa"), REML=TRUE) summary(modelLSI_maineff_RE) Error: number of observations (=1080) <= number of random effects (=1479) for term (1 + Index1 + LSI | ID); the random-effects parameters and the residual variance (or scale parameter) are probably unidentifiable I did test...

...ot under Windows. Anyone knows why? Thanks. > example(lmer) lmer> (fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy)) Error in UseMethod("as.logical") : no applicable method for "as.logical" > traceback() 9: as.logical(EMverbose) 8: as.logical(EMverbose) 7: lmerControl() 6: do.call("lmerControl", control) 5: lmer(Reaction ~ Days + (Days | Subject), sleepstudy) 4: eval.with.vis(expr, envir, enclos) 3: eval.with.vis(ei, envir) 2: source(zfile, local, echo = echo, prompt.echo = paste(prompt.prefix, getOption("prompt"), sep = ""),...

...he code below to run my model using lmer. However, > I get the following error. Please let me know how I can solve this error. > Please note that I have 50% missing data in SA at age 12. > modelLSI_maineff_RE <- lmer(SA ~ Index1* LSI+ (1 + Index1+LSI |ID), data = > LSIDATA, control = lmerControl(optimizer ="bobyqa"), REML=TRUE) > summary(modelLSI_maineff_RE) > Error: number of observations (=1080) <= number of random effects (=1479) > for term (1 + Index1 + LSI | ID); the random-effects parameters and the > residual variance (or scale parameter) are probably uniden...

...he code below to run my model using lmer. However, > I get the following error. Please let me know how I can solve this error. > Please note that I have 50% missing data in SA at age 12. > modelLSI_maineff_RE <- lmer(SA ~ Index1* LSI+ (1 + Index1+LSI |ID), data = > LSIDATA, control = lmerControl(optimizer ="bobyqa"), REML=TRUE) > summary(modelLSI_maineff_RE) > Error: number of observations (=1080) <= number of random effects (=1479) > for term (1 + Index1 + LSI | ID); the random-effects parameters and the > residual variance (or scale parameter) are probably uniden...

...st by Doug Bates). So I did: fm2 <- lmer(resistance ~ ET + position + (1|Grp), Semiconductor,method='ML') simdata<-simulate(fm2,nsim=1) ynew <- simdata[,1] mer <- fm2 .Call("mer_update_y", mer, ynew, PACKAGE = "Matrix") mer1u <- LMEoptimize(mer, lmerControl(mer)) What puzzles me is that this call alters my original model fm2 as some kind of side effect. In fact, after the call fm2 is the same as mer1u. Is this side effect intentional and is it possible to avoid? A detail is that "LMEoptmize" and "LMEoptimize<-" are not exporte...

...a.action, offset, contrasts = NULL, model = TRUE, matDimI = matDim, rand_matI = rand_mat, ...) { method <- match.arg(method) formula <- as.formula(formula) if (length(formula) < 3) stop("formula must be a two-sided formula") cv <- do.call("lmerControl", control) mc <- match.call() fr <- lmerFrames(mc, formula, data, contrasts) if (matDimI[1] != length(fr$Y)) stop("forSmoothing is not a sensible length") #insert Y <- fr$Y X <- fr$X weights <- fr$weights offset <...