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...Our group's aim is to find if the expression staining of a particular gene in a sample (or "core") is related to the pathology of the core. To do this, we used the lmer function to perform a logistic mixed model below. I apologise in advance for the lack of subscripts. logit P(yij=1) = â0 + Ui + â1Patholij where Ui~N(0, óu2), i indexes patient, j indexes measurement, Pathol is an indicator variable (0,1) for benign epithelium versus cancer and yij is the staining indicator (0,1) for each core where yij equals 1 if the core stains positive and 0 otherwise. (I have inse...

Suppose I have a mixed-effects model where yij is the jth sample for the ith subject: yij= beta0 + beta1(age) + beta2(age^2) + beta3(age^3) + beta4(IQ) + beta5(IQ^2) + beta6(age*IQ) + beta7(age^2*IQ) + beta8(age^3 *IQ) +random intercepti + eij In R how can I get an F test against the null hypothesis of beta6=beta7=beta8=0? In SAS...

I'm hoping that this is a relatively easy question for someone familiar with the lme4 package. I'm accustomed to using HLM software and writing a simple 2 level [null] equation like this: L1 - Yij = b0 + e L2 - b0 = B00 + u0 The following command in R provides results that are identical to the HLM program. results <- lmer( Y ~ 1 |id , PanelData4) I can't seem to find any examples on-line nor in the help about how to write the lmer4 formula that contains two predicto...

...(i) = i * 2 ^ Invalid declaration of or reference to symbol `forall' at (^) [initially seen at (^)] ... ----end output ---- The code compiles using: gfortran -c estimate.f I can run my code if I build the .so by hand and then dyn.load it. Here is my F95 test code: subroutine estimate(beta, yij, nij, nxrows, nxcols,xmat, & irequest, ierror) integer nxrows, nxcols, yij, nij, irequest, ierror double precision beta(nxrows), xmat(nxrows,nxcols) integer i i = 0 c fortran 95 version forall (i = 1:nxrows) beta(i) = i * 2 ierror = 0 end Regards, Joel Bremson UC Davis [[alternative HTM...

...ta.frame with the following colnames pattern: x1 y11 x2 y21 y22 y23 x3 y31 y32 ... I.e. I have an x followed by a few y's. What I would like to do is turn this wide format into a tall format with two columns: "x", "y". The structure is that xi needs to be associated with yij (e.g. x1 should next to y11 and y12, x2 should be next to y21, y22, and y23, etc.). x y x1 y11 x2 y21 x2 y22 x2 y23 x3 y31 x3 y32 ... I have looked at ?reshape but I didn't see how it could work with this structure. I have a solution using nested for loops (see below), but it's slo...

Hi everyone, I would like to ask a question regarding to the data used to fit the mixed model. I wonder that, for the response variable data used to fit the mixed model (either via "spm" or "lme"), we must have several observations per subject (i.e. Yij, i = 1,..,M, j = 1,.., ni) or it can be just one observation per subject (i.e. Yi, i = 1,...,M). Since we have to specify the groups for random effect components, if we have only one observation per subject, then each group will have only one observation. Thank you vert much for your help. S...

Dear All, I wonder if there is an efficient way to fit the generalized linear mixed model for multivariate outcomes. More specifically, Suppose that for a given subject i and at a given time j we observe a multivariate outcome Yij = (Y_ij1, Y_ij2, ..., Y_ijK). where Y_ijk is a binomial(n_ijk, p_ijk). One way to jointly model the data is to use the following specification: g(p_ijk) = beta_0k + b_0ik + (beta_1k + b_1ik)*x_ijk with k = 1,2 ...., K , g is a specified link function and (b_0ik,b_1ik) k=1,...K are random eff...

...ory allocation failed (R exits in terminal, or freezes as GUI) However, if I import a data element the rtest runs fine. I know rtest() doesn't need the extra data import because it runs without problems on our OS X version. > library("bpkg") .onLoad: running R_g95_init > data(yij) > o = rtest() Testing cm.estimate... Using short data set (testing)... 25500.0000000000 2499.00000000000 11.0000000000000 300.000000000000 ... 6 0.000000000000000 Done > (R continues to run without problems) The default rtest runs a short data set because the full test data set takes abo...

Hello. A quick question about incorporating variation due to study in the metafor package. I'm working with a particular data set for meta-analysis where some studies have multiple measurements. Others do not. So, let's say the effect I'm looking at is response to two different kinds of drug treatment - let's call their effect sizes T1 and T2. Some studies have multiple

...preciated. Note that YEAR will be treated as a factor and not a linear variable (i.e., the relationship between COUNT and YEAR is not linear - rather there are highs and lows about every 10 or so years). One thought I did have was to just set up a loop to calculate the least-squares estimates as: Yij = (IYi + JYj - Y)/[(I-1)(J-1)] where I = number of treatments and J = number of blocks (so I = sites and J = years). I found this formula in some stats lecture handouts by UC Davis on unbalanced data and LSMeans...but does it yield the same thing as using the LSmeans estimates? Does it make any se...

...ple at bottom] I have regional migration flows (?samples?) from, say, regions A to B, A to C, B to A, ?., C to B (Noted as xIJ in my example). Each of these is a time series, but I want to use R?s time series tools to fit an ARIMA (or ARMA) model along with some independent variables (Noted as YIJ, ZIJ, where Y and Z are characteristics (e.g., per capita GDP), I indicates the region, and J in {O, D} indicates whether it is the origin or destination region). I can do this easily enough for a single flow, say from A to B. But what if I want to find one set of coefficients for all of the...

getting this error compile error /Users/bradwrage/webapps/blog/app/views/posts/index.html.erb:5: syntax error, unexpected ''='' ...w Goal", new_post_path, class="btn btn-success" );@output_bu... ^ /Users/bradwrage/webapps/blog/app/views/posts/index.html.erb:7: syntax error, unexpected kDO_BLOCK, expecting kEND ''); @posts.each

...LMM, GLM, and GLMM and their standard errors. Also, I am trying to estimate the variance components and their standard errors. Further, I am trying to use the likelihood ratio test to test H0: sigma^2_b = 0 (random effects variance component), and the t-test to test H0:mu=0 (intercept of the model Yij = mu + Bi + Eij). I am using the following program all.fix.coef.lme <- rep(NA,R) all.fix.coef.lm <- rep(NA,R) all.fix.coef.glm <- rep(NA,R) all.se.fix.coef <- rep(NA,R) all.fix.coef.glmm <- rep(NA,R) all.se.fix.coef.glmm <- rep(NA,R) all.varcomp.g <- rep(NA,R) all.se.varc...

...cXXl5Ee5uO5y8rf4azp9k/9Wp2+A5kB/ hL8WznFSWQLshDo2UBtoAewG/nLX4BSnVpbMDyFITuACQClgKqABsA1g5If4oHCLMwWNHKQj2JFO HqZPdPpLetRMvgVOn6cCOaYI5Bl/DTigPcoeD/d5du6CKJBn6w5wAnnu3AJOIM+t68EJ5Fm0ApxA npYF4ATyzG4AJ5Bnag04oAh/6IXBQ5xFUxcypSyJr0SUViJKKxGllSTjNgaFvpbFGH8RHjYMEdvt 8w4d5gweYMEXWXAGCz7Kgq0suJYF17NgMQveyIJeFnSwYA4L+ljwIM5RRkHm675CHOezs+ARFnyG BTtY0MOCuSw4mAUVVuSLcFf4WmwsEL9OusrEvuKurmtKCpMwRhci6kJau7DtDwEfA2i65IOTMijq nJkj6KCuYaVRefj4wiVlk/hhVDyMZThMZwAyFugw0ugwGjmM5pKASwENgB7ABYAGMMJ7EOaxTcdJ wAWAUkADYB3gAsCoD+cChsJpCbAY4nP6wAqASwFThcQPo4jrLhd3+QbaHDavbZK0zcGSctjUHC2H F1F6Oo65lGRzcoRZ931l/ddXVoori+N...

I have data that looks like this: > df1 group id 1 red A 2 red B 3 red C 4 blue D 5 blue E 6 blue F I want a list of the groups containing vectors with the ids. I am avoiding subset(), as it is only recommended for interactive use. Here's what I have so far: df1 <- data.frame(group=c("red", "red", "red", "blue",

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Hi there, I'm having trouble to compile the R + C/C++ codes for this project from Yahoo folks on latent factor models: https://github.com/yahoo/Latent-Factor-Models#readme After downloading the package from the site, I could not successfully *make* the files. Here is the message: ====================================================================================== sh-4.1$ make R CMD