similar to: about the cox result

Hi all: There's a question about glht function. My data:data_ori,which inclue CD4, GROUP,time. f_GROUP<-factor(data_ori$GROUP) f_GROUP is a factor of 3 levels(0,1,2,3) result <- lme(sqrt(CD4) ~ f_GROUP*time ,random = ~time|ID,data=data_ori) glht(result, linfct = mcp(f_GROUP="Tukey") ) Error in `[.data.frame`(mf, nhypo[checknm]) : undefined columns selected I can't

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

Hi all: My data has 3 variables: age(3levels : <30y=1 30-50y=2, >50y=3) gender(Male=0, Female=1) CD4 cell count(raw lab measurement) y(1:death 0:alive) I perform logistic regression to find out the factors that influence y. result<-glm(y ~ factor(age) + factor(gender) + CD4,family = binomial) >From the result,I can get OR(Odds Ratio) of gender via exp(Estimate of Female,

Hi folks... check this out.. > GLU<-lme(gluc~rt*cd4+sex+age+rf+nadir+pharmac+factor(hcv)+factor(hbs)+ + haartd+hivdur+factor(arv), + random= ~rt|id, na.action=na.omit) > intervals(GLU)$fixed lower est. upper (Intercept) 67.3467070345 7.362307e+01 7.989944e+01 rt *0.0148050160* 6.249304e-02 1.101811e-01 cd4

Hi, Am I interpreting the results properly? Are my conclusions correct? > KPSS.test(df) ---- ---- KPSS test ---- ---- Null hypotheses: Level stationarity and stationarity around a linear trend. Alternative hypothesis: Unit root. ---- Statistic for the null hypothesis of level stationarity: 1.089 Critical values: 0.10 0.05 0.025 0.01 0.347 0.463

Hi all,I have some questions about the covariants of regression. My target: To explore the trend of CD4 level through a period of time. Response variable: CD4 count Explanatory variable:time Also, the demology information is available,such as gender,occupation,income level... Q1,Are these variables of demology information called covariant? Q2,How can I correct the impact of

Hi, How can I access the Values stored in kpssstat-class given by KPSS.test function and store it in a variable. For example: >x <- rnorm(1000) >test <- KPSS.test(ts(x)) >test ---- ---- KPSS test ---- ---- Null hypotheses: Level stationarity and stationarity around a linear trend. Alternative hypothesis: Unit root. ---- Statistic for the null

Hello! I need some help with creating plots for each study subject. I have tried the 'for' command as described in 'An Introduction to R', but I wasn't successful. Here's what I want to do: -Create and save the following overlayed scatterplots for each subject (1 to n). -The data frame is in the form of one line per visit per subject (so more than one line per

Hi dears while modeling an interaction random effect in lmer i receive the instantaneous error message > ldlM4<-lmer(ldl~rt*cd4+age+rf+pharmac+factor(hcv)+ + hivdur+(rt:cd4|id),na.action=na.omit,REML=F) *Warning message: In mer_finalize(ans) : false convergence (8) * I think the matter lies in syntax, 'cause i sistematically receive the same message even when changing response... PS:

Hello, I am working from a linux 64 machine on a server with R-2.12 (I can't update to 2.13). I am iterating through many linear mixed models for longitudinal data and I occasionally receive the following convergence error: > BI.lme <- lme(cd4 ~ time + genBI + genBI:time + C1 + C2 + C11 + C12, random =~ 1 + time | IID, data = d) Error in lme.formula(cd4 ~ time + genBI + genBI:time +

Hi I am using the flowClust package from BioConductor, which is largely implemented in c. For some of my data, the package occasionally (and quite stochastically) encounters a particular condition which halts its operation. At this point, it calls the error() function defined by Rcpp, and halts. What I would like to be able to do is to catch the error thrown, and retry the operation a few

Hi All, A newbie question :-( How do I go about installing the add-ons found in CD4? Many thanks, Joao -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.centos.org/pipermail/centos/attachments/20050205/8c4f13bc/attachment-0005.html>

Hi all: I have a question about linear mixed model. my linear mixed model with randomized slope and intercept with interaction of time and group(g1,g2,g3): model<- glmmPQL(log10(CD4) ~ time + factor(group)+ time:factor(group), random = ~time|id) What I get is only the main and interaction of time and group.My question is: 1. How can I get the g1,g2,g3's slope respectively?In other

Is anyone getting a yum update problem with glibc and glibc-common? I'm getting the error message ------------------------------- Error: Protected multilib versions: glibc-2.12-1.47.el6_2.12.x86_64 != glibc-2.12-1.47.el6_2.9.i686 ** Found 3 pre-existing rpmdb problem(s), 'yum check' output follows: bash-4.1.2-9.el6_2.x86_64 is a duplicate with bash-4.1.2-8.el6.centos.x86_64

Hi: I am using a subset of the below dataset to predict PRED_SUIT for the whole dataset but I am having trouble with 'newdata'. The model was created with 153 records and want to predict for 208 records. wolf2 <- structure(list(gridcell = c(367L, 444L, 533L, 587L, 598L, 609L, 620L, 629L, 641L, 651L, 662L, 674L, 684L, 695L, 738L, 748L, 804L, 805L, 872L, 919L, 929L, 938L, 950L, 958L,

I currently work on a draft of an aquatic bioassessment. The conditions tested are the following: ER river water T dechlorinated water control 0.5 + 0.5mg / L of malate T + 1 dechlorinated water control + 1g / L of malate T ED dechlorinated water control SED + ER + river water sediment SED ED + sediment + water dechlorinated. It is the result of AChE in muscle (fillet of fish). The production of

I have a 45 x 16 data frame consisting of dissimilarities among 10 colors, giving in each column the 45 = 10*9/2 pairwise judgments for one of 16 subjects. The rownames identify each pair of colors, e.g, "AC" = ("A","C"), and the pairs are ordered by columns in the lower triangle of each distance matrix. > helm.raw <-

Hello, Apologies if this is the wrong list, I am a first-time poster here. I have an experiment in which an output is measured in response to 42 different categories. I am only interested which of the categories is significantly different from a reference category. Here is the summary of the results: summary(simple.fit) Call: lm(formula = as.numeric(as.vector(TNFa)) ~ Mutant.ID, data =

Hi all, I'm seeing this failure on my PPC G4 box running TOT with llvm-gcc 4.2. Is anyone else seeing this? I'm sure it's related to the byval stuff that's recently gone into LLVM. I'm attaching the output of this command: $ llvm-gcc -emit-llvm -O3 -S -o - -emit-llvm /Users/wendling/llvm/ llvm.src/test/CFrontend/2008-01-25-ByValReadNone.c As you can see in it, there

Dear R users I have a big matrix like 6021 1188 790 290 1174 1015 1990 6613 6288 100714 6021 1 0.658 0.688 0.474 0.262 0.163 0.137 0.32 0.252 0.206 1188 0.658 1 0.917 0.245 0.331 0.122 0.148 0.194 0.168 0.171 790 0.688 0.917 1 0.243 0.31 0.122 0.15 0.19 0.171 0.174 290 0.474