similar to: Intercepts is coming as Zero in the Mixed Models

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

Hi, I want to remove the entire row from the dataset if any of the row contains blank or NA my dataset look like State Year Y X2 X3 X4 X5 X6 State1 1960 27.8 397.5 42.2 50.7 78.3 65.8 State2 1960 29.9 413.3 38.1 52 79.2 66.9 State1 1961 29.8 439.2 40.3 54 79.2 67.8 State2 1961 30.8 459.7 39.5 79.2 69.6 State1 1962 31.2 492.9 37.3 54.7 77.4 68.7 State2 1962 528.6 38.1 80.2 73.6 State1 1963

I recently replaced a 8600 GT with the above card on openSUSE Tumbleweed x86_64. The screen now flickers and when I change desktops it takes a some 10 to 15 seconds to display the new windows. e.g if I change from desktop 1 (konsole) to desktop 8 (thunderbird) it switches but konsole is displayed for 10 to 15 seconds before thunderbird appears. Occasionally the screen flickers wildly before

Please provide your dmesg and xorg logs from the affected machine. Thanks, -ilia On Wed, Jun 29, 2016 at 8:17 AM, Sid Boyce <sboyce at blueyonder.co.uk> wrote: > I recently replaced a 8600 GT with the above card on openSUSE Tumbleweed > x86_64. > > The screen now flickers and when I change desktops it takes a some 10 to 15 > seconds to display the new windows. > e.g if

Dear R users, I have more of a statistical/econometric question than straight R one. I have a data set with the discrete hazard rate of small firms survival on 400 counties over a period of 9 years. This data was generated using census information from the VAT registration number of each one of these business. I would like to analyze the effect of regional factors (deprivation index, real

https://bugs.freedesktop.org/show_bug.cgi?id=38016 Summary: nouveau driver crashes xorg when starting KDE Product: xorg Version: git Platform: Other OS/Version: All Status: NEW Severity: normal Priority: medium Component: Driver/nouveau AssignedTo: nouveau at lists.freedesktop.org

Hello all, I need to infer if the slopes and intercept of each group of my lme analyze, showed below, are different from each other. Like a Tukey test. I don't need to compare the slope and interceptof each subject of my fixed data, but the slope and intercept of each group of them. > m1<-lme(fvfm~term*sp*env*est*time,random=~term|id,table) You know how can I make it? Thanks for

Hi, I search online and find rpar argument to specify random effect for independent variables. Is there a way to specify that for intercepts too? Thanks, Aaron Management, PhD Stanford University [[alternative HTML version deleted]]

David Stoffer describes some challenges with R's output when fitting ARIMA models for different orders (see Issue 2 at http://www.stat.pitt.edu/stoffer/tsa2/Rissues.htm). R doesn't fit an intercept in the model if there is any differencing. David describes a workaround using the xreg parameter to force R to calculate an intercept. Assume I have a variable y and 3 explanatory variables a,

mgcv: Constructing probabilities for binomial GAM with crossed random intercepts and factor by variable Hello, (I'm sorry if this has been discussed elsewhere; I may not have been looking in the right places.) I ran a binomial GAM in which "Correct" is modelled in terms of the participant's age and the modality in which the stimulus is presented (written vs spoken).

Hi all: I perform the linear mixed model for 300 persons, y is CD4 count,x is time. I randomized slope and intercept,so I can get 300 slopes and 300 intercepts.Now I wanna test wheter the variance of 300 slopes and 300 intercepts differs from zero. If the variance of 300 slopes(or intercepts) differs from zero at 0.05 significant level,I should randomize the slope(or intercept), and if not,I

Hi everyone, I have been using REML to derive intercepts and coeficients for each individual in a growth study. So the code is m2 <- lmer(change.wt ~ newwt+(newwt|id), data = grow) Calling coef(model.lmer) gives a matrix with this information which is what I want. However, as a test I looked at each individual on its own and used a simple linear regression to obtain the same information, then

A colleague asked me if there is a way to specify with a ***variable*** (say ``cflag'') whether there is an intercept in a linear model. She had in mind something like lm(y ~ x - cflag) where cflag could be 0 or 1; if it's 0 an intercept should be fitted, if it's 1 then no intercept. This doesn't work ``of course''. The cflag just gets treated as another predictor

I posted this question way down at teh end of another thread realted to an error in step, but that was stupid since it really is another matter altogether. I should have posted it separately, as I have now done. The code below creates a data.frame comprising three marginally noisy surfaces. The code below (including a fix courtesy of David Winsemius that avoids a step function error through use

I fit the model fit<-lm(thresh~cond*Ne) where thresh is the reponse cond is a factor with levels a, b, and c Ne is a continuous indep var I think of this full model as having three lines: thresh as a function of Ne for each condition. Thus we have slopea, slopeb, slopec, inta, intb, intc. lm output my params ------------------------- (Intercept) inta condb intb - inta condc

From: Carsten Otte <cotte at de.ibm.com> From: Christian Borntraeger <borntraeger at de.ibm.com> This patch introduces interpretation of some diagnose instruction intercepts. Diagnose is our classic architected way of doing a hypercall. This patch features the following diagnose codes: - vm storage size, that tells the guest about its memory layout - time slice end, which is used by

Can you provide the summary(m2) results? > -----Original Message----- > From: Simon Pickett [mailto:S.Pickett at exeter.ac.uk] > Sent: Wednesday, August 16, 2006 7:14 AM > To: Doran, Harold > Cc: r-help at stat.math.ethz.ch > Subject: [SPAM] - RE: [R] REML with random slopes and random > intercepts giving strange results - Bayesian Filter detected spam > > Hi again,

From: Carsten Otte <cotte at de.ibm.com> From: Christian Borntraeger <borntraeger at de.ibm.com> This patch introduces in-kernel handling of some intercepts for privileged instructions: handle_set_prefix() sets the prefix register of the local cpu handle_store_prefix() stores the content of the prefix register to memory handle_store_cpu_address() stores the cpu number of

Hi All, We have a single Centos 5.11 server running a xen hypervisor that went down hard after an extended power outage this weekend. I'm mostly familiar for KVM as that is the majority of what our guests run under and have tried getting up to speed on xen bridging to no avail. The problem is that after the xen server spun back up, the previously defined xen bridges were lost. I've

I would like to be able to shade between two lines using ggplot2 (with faceting too). But, despite reading all the documentation on the website, cant figure out how to do it (either because i am a novice or idiot - or, of course, possibly both) My data looks is readership of paid & free newspapers in london by age since 1994. The structure is reading.melt <- structure(list(Date =