similar to: Meta-analysis mixed model

Hello all, I've got a large set of data consisting of 2 continuous numerical variables, and 2 factors. I'm trying to write a function that will draw scatter plots of the 2 numerical variables for various combinations of the factors. The problem is that my function doesn't seem to understand what I want it to do even though the command works fine outside the function. Here is

Hello all, I am having a problem using augPred after I have created an nlme object. My data is 3933 rows long with no NA's, and is grouped with this function: vanfem<-groupedData(mass~age.years|name, data=av.mex, labels=list(x="Age", y="Mass"), units=list(x="(years)", y="(kg)")) Under the grouping factor "name", this is a character

Hello, I can not get the function plot.logistic.fit.fnc() working....it returns "Error: could not find function "plot.logistic.fit.fnc"". Do I need to upload as specific package first? I am trying to check the fit of a mixed logistic model. Also, any advice for checking the assumption of independence in a mixed logistic model? Many thanks in advance, Sarah Foster

Dear list I am sorry to have to ask this question, but I have not been able to find a solution to what seems a simple problem. I have created a lattice plot of a number of regression points and lines using a function containing panel.xyplot and panel.lmline. The result is what is expected , but I cannot figure out how to obtain the coefficients of each of the regression lines. Any help

Hi, Has anyone successfully implemented the :onsubmit option for form_remote_tag. It doesn''t seem to work for me. Is there any specific version of rails which is required for the same. Here''s my piece of code. <script> function set_tojid(){ alert(''onsubmit''); } </script> <%= form_remote_tag :update => '''', :url => {

Dear Wolfgang Viechtbauer and list members: I have discovered your "MiMa" function for fitting meta-analytic mixed-effects models through an earlier discussion on this list. I think it is extremely useful and fills an important gap. In particular, since it is programmed so transparently, it is easy to adapt it for one's own needs. (For example, I have found it easy to identify

R-experts: In 2002, Hans Van Houwelingen et al. published a tutorial on how to do meta-regression in Statistics in Medicine. They used the classic BCG dataset of Colditz to demonstrate correct methodology and computed the results using PROC MIXED in SAS. In trying to duplicate the results presented in this paper, I have discovered that I can reproduce certain items with lmer but not

Hello R users, I'm a newby to R (and programming software at large) and I would need some help to sum up event data at discreet time and irregular time interval into a hourly frequency. Here is an example of my time series frame (irregular time-serie object - irts in the tseries package): time value 2008-12-19 19:11:03 GMT 1 2008-12-19 19:12:00 GMT 0 2008-12-19

Dear R-helpers, I'm trying to associate linear coefficients (intercept and slope) to tens of thousands of observations based on a table with benchmark values. #####Example - Value table and their corresponding coefficients (intercept and slope) coef = data.frame(cbind(st=c(1:5),b = runif(5,0.3,5),a = seq(0.5,5,1)))print(coef) #Example of observations to be computedobs = runif(20,1,5)print(obs)

I had found the author's (Wolfgang Viechtbauer) earlier meta-analytic code in R, MiMa, useful. so I have been exploring metafor using an example dataset from MiMa. metafor provides a lot more. However, MiMa provided parameter estimates, standard errors, z values, etc. for individual moderators in the meta-analysis, but I don't see how to obtain these from metafor. Have you any help

Dear R Friends, I need help with an error associated with corCompSymm in an lme fit. I am using a mixed effects model to analyze a split-plot with repeated measures and would like to fit with the compound symmetry correlation structure. This problem doesn't occur when using corAR1 or any of the other structures. I would greatly appreciate help on how to solve this issue. Here's my

Hi, I am not been able to contact with mentor of this project. Can someone else from the community help me with this ? Regards, Anusha Srivastava On 3 March 2018 at 11:16, Anusha Srivastava <sidd.sinha89 at gmail.com> wrote: > Hi Martin, > > Any update on this ? > Regards, > Anusha Srivastava > > > On 28 February 2018 at 23:37, Anusha Srivastava <sidd.sinha89

Hi Anusha, Sorry, I was under the expectation that userspace developers would answer you after your first message, and I missed your second one! My sincere apologies. Generally, the process is that the student should research the topic by first asking questions to developers about the effort, then they would make their own plan. Then you would present this plan while looking for a mentor. Of

I would like to combine time-series data to test for correlations and interactions using random and fixed effects meta-analysis. So, I am looking for the right packages and documentation. I know about meta and rmeta packages of R. Are there any more? What are the diffrences in brief? Can you please suggest some references that could be used as a guide for meta-analysis in R (or S-plus)?

On Fri, May 4, 2012 at 6:50 PM, vaibhav srivastava <vaibhavcse30 at gmail.com>wrote: > > Hi all, > Since I want to run Samba without modifying my existing kernel. Please > tell me what are the requirements for the same. > What are the package list required in kernel before installing samba. > thanks in advance. > -- > Thanks and Regards, > Vaibhav Srivastava >

Dear List, I am (again) looking at meta-regression as a way to refine meta-analytic results. What I want to do is to assess the impact of some fixed factors on the results of a meta-analysis. Some of them may be crossed with the main factor of the meta-analysis (e. g. clinical presentation of a disease, defining subgroups in each of the studies under analysis), some of them may be a grouping

Hi, I'm having a problem using LME and hopefully I can get some help. Here is what I'm doing: I have a model like this: yi = alpha + theta * xi + beta * zi + error, errors are normally distributed mean 0, var sigma^2 xi and zi are generated from normal distributions within a specified range. True values of alpha, theta, beta and sigma^2 are chosen with a specific mean and variane

Hi, I am trying to understand the alternative methods that are available for selecting variables in a regression without simply imposing my own bias (having "good judgement"). The methods implimented in leaps and step and stepAIC seem to fall into the general class of stepwise procedures. But these are commonly condemmed for inducing overfitting. In Hastie, Tibshirani and Friedman

Hi Martin, Any update on this ? Regards, Anusha Srivastava On 28 February 2018 at 23:37, Anusha Srivastava <sidd.sinha89 at gmail.com> wrote: > Hi, > > I would like to participate in GSOC 2018 with Xorg to contribute to > project "Initial Nouveau Vulkan driver' > I would need some help in how to get started with the same. > > Regards, > Anusha Srivastava

Dear colleagues, I'm conducting a meta-analysis of studies evaluating adherence of HIV-positive drug users into AIDS treatment, therefore I'm looking for some advice and syntax suggestion for running the meta-regression using proportions, not the usual OR/RR frequently used on RCT studies. Have already searched already several handbooks, R-manuals, mailing lists, professors, but... not