similar to: pdMat class in LME to mimic SAS proc mixed group option? Group-specific random slopes

Dear members, I would like to switch from nlme to lme4 and try to translate some of my models that worked fine with lme. I have problems with the pdMat classes. Below a toy dataset with a fixed effect F and a random effect R. I gave also 2 similar lme models. The one containing pdLogChol (lme1) is easy to translate (as it is an explicit notation of the default model) The more parsimonious

Dear All, I wish to model random effects that have known between-group covariance structure using the lme() function from library nlme. However, I have yet to get even a simple example to work. No doubt this is because I am confusing my syntax, but I would appreciate any guidance as to how. I have studied Pinheiro & Bates carefully (though it's always possible I've missed

Alguien tiene experiencia en escribir una pdMat. Para aquellos que no lo recuerden son las matrices de covarianzas de los efectos aleatorios que ajusta la función lme de la librería nlme Estas matrices tiene especial importancia en aplicaciones de genética de poblaciones y en particular en mapeo de asociación. Pinheiro y Bates dicen que el usuario puede crear sus propias pdMat y sugiere como

Hello. I want to specify a diagonal structure for the covariance matrix of random effects in the lme() function. Here is the call before I specify a diagonal structure: > fit2<-lme(Ln.rgr~I(Ln.nar-log(0.0011)),data=meta.analysis, + random=~1+I(Ln.nar-log(0.0011)|STUDY.CODE,na.action=na.omit) and this works fine. Now, I want to fix the covariance between the between-groups slopes

Hello. I know how to make a bar plot in which a numeric y variable is plotted against some grouping variable X (say, groups A, B, C) when this grouping variable is subdivided into each of two subgroups; so the bars would be: (group A subgroup 1) beside (group A subgroup 2), then (group B subgroup 1) beside (group B subgroup 2), and so on. This is done using the beside=TRUE argument in the

How does one implement a likelihood-ratio test, to test whether the variances of the random effects differ between two groups of subjects? Suppose your data consist of repeated measures on subjects belonging to two groups, say boys and girls, and you are fitting a linear mixed-effects model for the response as a function of time. The within-subject errors (residuals) have the same variance in

Dear R-ers, In my question there are no statistics involved - it's all about data manipulation in R. I am trying to write a code that should replace what's currently being done in SAS and SPSS. Or, at least, I am trying to show to my colleagues R is not much worse than SAS/SPSS for the task at hand. I've written a code that works but it's too slow. Probably because it's

Hello, I'm using the rmeta package to perform a meta analysis using summary statistics rather than raw data, and would like to analyze the effects in three different subgroups of my data. Furthermore, I'd like to plot this on one forest plot, with corresponding summary weighted averages of the effects displayed beneath each subgroup. I am able to generate the subgroup analyses by simply

Hello, ? I am struggling with a lattice graph. I want to plot points and condition on a variable called 'Method'. For each conditional plot I have two subgroups, say: 'first'and 'second'. I want to plot the points in a conditional graph with a different color or symbol for each subgroup. ? Moreover I want to calculate within each conditional graph limits of the points

I have a nice hierarchical table structure like this: divisions has_many groups groups belongs_to division has_many subgroups subgroups belongs_to group has_many units units belongs_to subgroup I have a report which is based on units, but i want to be able to filter the units by which subgroup, or which group, or which division. I also want to sort them by division.name,then group.name,

Dear R-users, I want to multiple impute missing scores, but only for a few subgroups in my data (variable 'subgroups': only impute for subgroups 2 and 3). Does anyone knows how to do this in MICE? This is my script for the multiple imputation: imp <- mice(data, m=20, predictorMatrix=pred, post=post, method=c("", "", "", "",

Hello everbody, I want to generate different subsets of my data-set and safe this subsets with names listet in a vector. Because in reality I have got about 70 subsets I want to realize this in a loop Somehow like this: names=c("nam1",

Hi All, Is there a feasibility for creating subgroups on the Puppet Dashboard? Basically the requirement is that we have a huge number of VMs running designated services. Some of VMs having the same service may yet have different properties configured on them. We are exploring the feasibility of having these properties managed through puppet. Currently all these VMs are put into a single

Hi, I have a data.frame with many variables for which I am performing the mean by subgroup, for a pair of variables at a time, where one of them for each pair defines the subgroup. The subgroups in the x$cm1 are 0, 1 and 2. x ph1 cm1 0.2345 2 1.2222 1 2.0033 0 0.0000 2 1.0033 1 0.2345 0 1.2222 2 2.0033 0 0.0000 1 1.0033 2 > meanbygroup <- as.vector(with(x, by(x$ph1, x$cm1, mean)))

[markdown format] I'm glad to introduce you the new package aVirtualTwins. This package is an adaptation of VirtualTwins method of subgroup identification from [Foster, J. C., Taylor, J. M.G. and Ruberg, S. J. (2011)](http://onlinelibrary.wiley.com/doi/10.1002/sim.4322/abstract). ### Explanation Virtual Twins has been created to find subgroup of patients in a random clinical trial with

[markdown format] I'm glad to introduce you the new package aVirtualTwins. This package is an adaptation of VirtualTwins method of subgroup identification from [Foster, J. C., Taylor, J. M.G. and Ruberg, S. J. (2011)](http://onlinelibrary.wiley.com/doi/10.1002/sim.4322/abstract). ### Explanation Virtual Twins has been created to find subgroup of patients in a random clinical trial with

With this mail I would like to make a proposal to add additional informations to the core and plugin metadata files. Currently these tags are already handled in the ccs configuration system. Ccs automatically adds this informations to the core/plugin option set, but I think that it would make more sense to add this to the official files, to allow similar features in other configuration

Hi, Is there is any way in ruby on rails where we show all my groups there subgroups with check boxes in tree structure way? e.g group A | ----Group A.1 | ----Group A.2 | ---------Group A.2.1 All with check boxes and subgroup opens when click on root ? -- Posted via

Dear Members of the R-Help, While using a R function - 'aggregate' that you developed, I become to have a question. In that function, > aggregate(x, by, FUN, ..., simplify = TRUE) I was wondering about what type of FUN I should write if I want to get "the most frequent value of the subgroup" as a summary statistics of the subgroups. I will appreciate if I can get

I have the following formula for a linear model: z <- lm(y~x + factor(a) + factor(b), data=NT2010) where a (groups) and b (Sub-groups) are categorical variables (factors), x is a continuous covariate, and y the response variable. Since b is nested within a, the formula can also be written as: z <- lm(y~x + factor(a) + factor(a)/factor(b), data=NT2010) and the same output is achieved