search for: index1

I am running a multilevel growth curve model to examine predictors of social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a continuous numeric variable. The age variable (Index1) has been coded as 0 for age 12, 1 for age 15 and 2 for age 18. I am currently using a time varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, to examine whether trajectory/variation in LSI predicts difference in SA trajectory. LSI is a continuous numeric variable and was gr...

I am running a multilevel growth curve model to examine predictors of social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a continuous numeric variable. The age variable (Index1) has been coded as 0 for age 12, 1 for age 15 and 2 for age 18. I am currently using a time varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, to examine whether trajectory/variation in LSI predicts difference in SA trajectory. LSI is a continuous numeric variable and was gr...

...59 schreef Srinidhi Jayakumar via R-sig-mixed-models <r-sig-mixed-models at r-project.org>: > I am running a multilevel growth curve model to examine predictors of > social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a > continuous numeric variable. The age variable (Index1) has been coded as 0 > for age 12, 1 for age 15 and 2 for age 18. I am currently using a time > varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, > to examine whether trajectory/variation in LSI predicts difference in SA > trajectory. LSI is a continuous numeric...

...59 schreef Srinidhi Jayakumar via R-sig-mixed-models <r-sig-mixed-models at r-project.org>: > I am running a multilevel growth curve model to examine predictors of > social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a > continuous numeric variable. The age variable (Index1) has been coded as 0 > for age 12, 1 for age 15 and 2 for age 18. I am currently using a time > varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, > to examine whether trajectory/variation in LSI predicts difference in SA > trajectory. LSI is a continuous numeric...

Hi, Trying to learn Search::Xapian and be better at perl at the same time, I'm stuck, at the DB_CREATE_OR_OPEN error. Perl says this: ~/dev/sandbox/Xapian-perl$ ./Index1-Xap.pl 100-objects-v1.csv db "db" is not exported by the Search::Xapian module Can't continue after import errors at ./Index1-Xap.pl line 7. BEGIN failed--compilation aborted at ./Index1-Xap.pl line 7. What I did was try to convert the python example code in to Perl. There's prob...

...ents being 4 matrices based on an logical index vector. is there a way to simplify what I'm doing to obtain the results in "mylist2"? I'd like something that would work on an arbitrary number of elements in "mylist". mylist <- list(matrix(1:9,3,3), matrix(10:18,3,3)) index1 <- c(TRUE,FALSE,TRUE) index2<- c(FALSE,TRUE,TRUE) mylist2 <- list(mylist[[1]][,index1], mylist[[1]][,index1==FALSE], mylist[[2]][,index2], mylist[[2]][,index2==FALSE]) Thanks in advance, Axel. [[alternative HTML version d...

Hi, When adding an index to another one using add_indexes I get duplicates even though I use the :key attribute. For example: def test_add_indexes_uniqueness index1 = Ferret::Index::Index.new(:key => :id) index2 = Ferret::Index::Index.new(:key => :id) # Add two items with same id index1 << {:id => 23, :data => "This is the data..."} index1 << {:id => 23, :data => "This is the new dat...

When I try to run the following non-linear regression with variables index1 and prl3: > beta = 4 > nls(index1~beta*(1/prl3),start = list(beta = 4)) I get this error message: Error in nls(index1 ~ beta * (1/prl3), start = list(beta = 4)) : REAL() can only be applied to a 'numeric', not a 'logical' I've got no clue as to the REAL() to which t...

...;, na.strings="NA", dec=".", strip.white=TRUE) attach(Dataset) require (nlme) with(Dataset, table(runnb, id, grp)) b.lvls <- table(Dataset$runnb) nb <- length(b.lvls) fit <- vector(mode="list", nb) for(i in 1:nb) fit[[i]]<- lme (trans1 ~ Index1 + grp, random = ~ 1 | id / grp , data = Dataset, na.action = "na.exclude") This (above) worked OK only I am having memory problems. I have a gig of RAM set at --sdi --max-mem-size=512M (complete version below) I am wondering if running the...

Hi everyone, I have 2 environments (2 different R sessions) as described below: Session 1: Name of the environment: "CrlmmInfo" Objects in the environment: index1: logical index - length 238304 index2: logical index - length 238304 priors: list of 4 - (matrix 6x6, 2 vectors of length 6, vector of length 2) - all num params: list of 4: centers [238304 x 3 x 2]: num scales [238304 x 3 x 2]: num N [238304 x 3]: num...

Hi everyone, I have 2 environments (2 different R sessions) as described below: Session 1: Name of the environment: "CrlmmInfo" Objects in the environment: index1: logical index - length 238304 index2: logical index - length 238304 priors: list of 4 - (matrix 6x6, 2 vectors of length 6, vector of length 2) - all num params: list of 4: centers [238304 x 3 x 2]: num scales [238304 x 3 x 2]: num N [238304 x 3]: num...

Inline. Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Wed, Oct 14, 2020 at 3:23 PM 1/k^c <kchamberln at gmail.com> wrote: Is which() invoking c-level code by chance, making it slightly faster > on average? > You do not need

Hi, I am trying to run a linear mixed effect model on data. I have 17 longitudinal subjects and 36 single subjects, and this is the code I'm using (below). So, INDEX1 is the column with brain volumns, and the predictors are gort and age, by time ID (time they were seen). I believe my data is set up the right way, but when I run it, I get DF for Intercept is 49, and DF for slope is 13? Why? lme.gort=lme(Volume ~ GORT_FLUENCY+AGE, random = ~ 1 | TIMEID, da...

...yidx1, align 4, !tbaa !0 Value *loadValue = pInst->getOperand(0); Type *vecTy = VectorType::get(Type::getDoublePtrTy(currF->getContext()), 2); Value *emptyVec = UndefValue::get(vecTy); Type* u32Ty = Type::getInt32Ty(currF->getContext()); Value *index0 = ConstantInt::get(u32Ty, 0); Value *index1 = ConstantInt::get(u32Ty, 1); Instruction *InsertVal = InsertElementInst::Create(emptyVec, loadValue, index0, ""); InsertVal = InsertElementInst::Create(emptyVec, loadValue, index1, ""); InsertVal->insertBefore(pInst); It turned out that the way I am doing is not right bec...

...test) [1] "GeneFeatureSet" attr(,"package") [1] "oligoClasses" > class(phenoData) [1] "standardGeneric" attr(,"package") [1] "methods" > eset <- rma(test) Background correcting Normalizing > e <- exprs(eset) > index1 <- 1:5 > index2 <- 6:10 > d <- rowMeans(e[, index1]) - rowMeans(e[, index2]) > design <- model.matrix(~factor(eset$Key)) > fit <- lmFit(eset, design) > ebayes <- eBayes(fit) > sample <- row.names(ebayes) > Pvalue <- ebayes$p.value[,2] > Mean1...

Dear list, I'm trying to concatenate the values of two columns but im not able to do it: i have a dataframe with the following two columns: X VAR1 VAR2 1 2 2 1 3 2 4 3 5 4 6 4 what i would like to

...il to do the source-level debug on the executable. This issue is same in both Linux and Windows, and I figure out a simple case in Linux to reproduce this issue as below. Please help to give us some advices on how to solve the zero Lines issue. $ cat main.c void assembly_fun(); int main() { int Index1; for (Index1 = 0; Index1 == 0; assembly_fun(), Index1++){ assembly_fun(); } assembly_fun(); } $ cat assembly.nasm DEFAULT REL SECTION .text global assembly_fun assembly_fun: ret $ cat makefile_clanglto_Oz CC_FLAGS= -g -m64 -mcmodel=small -target x86_64-unknown-windows -gcodev...

...0???? 1.5?? NA?? 0.9 3??? 1???? 0.1?? 0.2?? 1.5 ...... .. My code is as follows: files <- list.files(pattern="*.raw") for(i in files){ of <- strsplit(i, "\\.")[[1]] of <- paste(head(of, 1)) data <- read.table(file=i, header=T) y<-data$PHI num<-length(y) index1<-c(1:num_sample)[y==1] index2<-c(1:num_sample)[y==0] gen<-as.matrix(data[,-c(1:2)]) source("pcc.R") # a function for my use out<- fpc_func(gen,num,index1,index2) out1<-as.data.frame(out) id1<-data[,2] id<- as.data.frame(iid1) out2<-cbind(iid1,out1) colnames(out2)...

Buenas, He creado dos andamios para dos tablas a la que accedo por index1 e index2 respectivamente. En cada index puedo hacer las tareas de añadir, borrar, ver lineas... pero me gustaria saber como se hace una busqueda mas compleja...es decir si tengo una tabla Productos y otra tabla descripciones y quiero mostrar en los productos con sus descripciones... he intentado en...

Is the phrase "index <- match(x, sort(unique(x)))" reliable, in the sense that it will never return NA? Context: Calculation of survival curves involves the concept of unique death times. I've had reported cases in the past where survfit failed, and it was due to the fact that two "differ by machine precision" values would sometimes match and sometimes not,