similar to: model comparison with mixed effects glm

Dear R community, I have a fairly large file with variables in rows. Every variable (thousands) needs to be regressed on a reference variable. The file is too big to load into R (or R gets too slow having done it) and I do now read in line by line with "scan" (see below) and write the results to out. Although improved, this is still very slow... Can someone please help me and suggest

Hello all, I have two comboboxen, comboA is popultaed when :controller/list is retrieved first time. When comboA is selected, I want to auto-populate comboB (modelB belongs_to modelA). The population of tableC (modelC belongs_to modelB and belongs_to modelA) should not populate until a "GO" button is clicked (link_to with submit). Help? I need an example of how to filter the post

Hello, I''m using find_with_ferret to search multiple models and it works great. The trouble is I need to filter the results using :include and :conditions. I get two errors depending on the syntax I use in the search. Reading the source, I see the retrieve_records method seems to filter the :include and :conditions so that they only apply to the relevant model when searching

Colleagues, I am trying to de-duplicate a large (long) database (approx 1mil records) of diagnostic tests. Individuals in the database can have up-to 25 observations, but most will have only one. IDs for de-duplication (names, sex, lab number...) are patchy. In a first step, I am using Andreas Borg's excellent record linkage package (), that leaves me with a list of 'pairs' looking

I have a template that belongs to a certain model (model A). I need to call a helper method of a different model (model B). Then I need the helper method of B to call a helper method of model C. I tried using "include" and "require" and using namespaces, but I got "undefined method". What is the way to do it? -- Posted via http://www.ruby-forum.com/.

Dear helpeRs- I'm using a for loop to create a series of models. I'm trying to assign a name to each model created, using the loop index. The loop gets stuck at the name of the model, giving the error "target of assignment expands to non-language object". The linear model runs without error; only the name is problematic. Here is the current loop syntax. The use of dat

Hi folks. If I am indexing ModelA and ModelB and I want to search both of them, I usually just pick one arbitrarily and use it for #multi_search. Is there a slicker pattern, regarding from which model to invoke #multi_search? Can it be invoked directly from the Ferret library? Has anyone put together some sort of "dummy" search class? Thanks for any ideas. John

Hi, I have here a problem I''ve been working at for a little while but I can''t seem to get the error messages to appear correctly. My form looks something like this for "ModelA": [errors_for "modelA"] [form for "modelA"] [text "modelA" "fieldname1"] [text "modelB" "fieldname2"] [submit] [/form] The reason

Hello, I have a problem concerning estimation of GLMM. I used methods from 3 different packages (see program). I would expect similar results for glmm and glmmML. The result differ in the estimated standard errors, however. I compared the results to MASS, 4th ed., p. 297. The results from glmmML resemble the given result for 'Numerical integration', but glmm output differs. For the

Dear all, I have tried to calculate a GLMM fit with lmer (lme4) and glmmPQL (MASS), I also used glm for comparison. I am getting very different results from different functions, and I suspect that the problem is with our dataset rather than the functions, but I would appreciate help in deciding whether my suspicions are right. If indeed we are attempting the wrong type of analysis, some

Dear R users, I'm hoping that more experienced users will be able to assist me in examining the model fit of a mixed generalised linear model. The example using the data 'bacteria' within the MASS package will hopefully illustrate what I would like to acheive; library(MASS) library(nlme) attach(bacteria) # y being output and the trt - treatment group being an explanatory variable.

Dear R users I encounter a problem when i perform a generalized linear mixed model (binary data) with the lmer function (package lme4) with R 2.1.0 on windows XP and the latest version of package "lme4" (0.96-1) and "matrix" (0.96-2) both options "PQL" and "Laplace" for the method argument in lmer function gave me the same results (random and fixed effects

Is the labeling/naming of levels in the documentation for the predict.glmmPQL function "backwards"? The documentation states "Level values increase from outermost to innermost grouping, with level zero corresponding to the population predictions". Taking the sample in the documentation: fit <- glmmPQL(y ~ trt + I(week > 2), random = ~1 | ID, family =

Hi, I was recently misfortunate enough to have to use regular expressions to sort out some data in R. I'm working on a data file which contains taxonomical data of bacteria in hierarchical order. A sample of this file can be generated using: tax.data <- read.table(header=F, con <- textConnection(' G9SS7BA01D15EC Bacteria(100) Cyanobacteria(84) unclassified G9SS7BA01C9UIR

FreeBSD psg.com 11.3-RELEASE-p3 FreeBSD 11.3-RELEASE-p3 dovecot 2.3.6 (7eab80676) (latest from binary package system) symptom: multiple imap4s users complain that they can not fetch mail stopping and restarting dovecot is a temporary workaround dovenull 3713 0.0 0.0 11036 6816 - I 02:27 0:00.17 dovecot/imap-login user19 3714 0.0 0.0 9464 4756 - S 02:27

I have a data frame that looks like this: > gctablechromonly[1:5,] refseq geometry gccontent X60_origin X60_terminus length kingdom 1 NC_009484 cir 0.6799 1790000 773000 3389227 Bacteria 2 NC_009484 cir 0.6799 1790000 773000 3389227 Bacteria 3 NC_009484 cir 0.6799 1790000 773000 3389227 Bacteria 4 NC_009484 cir 0.6799

Hello Everybody, I have an eps figure an awesome bacteria and a plot (generated using R) also in eps format. Now it looks like there is space for only one figure and I have to insert the picture of the bacteria into the plot. Is there a way to insert figures (eps/png/jpg) in to plots (may be control over placement of figures in the plot as well?) ? By plots I mean data represented using axes and

Has anyone programmed condition indexes in R? I know that there is a function for variance inflation factors available in the car package; however, Belsley (1991) Conditioning Diagnostics (Wiley) notes that there are several weaknesses of VIFs: e.g. 1) High VIFs are sufficient but not necessary conditions for collinearity 2) VIFs don't diagnose the number of collinearities and 3) No one has

Dear all, I am interested in correctly testing effects of continuous environmental variables and ordered factors on bacterial abundance. Bacterial abundance is derived from counts and expressed as percentage. My problem is that the abundance data contain many zero values: Bacteria <-

Dear List, I apologize in advance if this is silly. I tried to replicate an analysis I did previously in SPSS using R, and was surprised to find different results. So my question is: shouldn't the following SPSS syntax REGRESSION DEPENDENT INC89 /METHOD=ENTER hiedyrs experien SE93rec. Yeld the same results of the following R command modelB<-lm(INC89~HIEDYRS+EXPERIEN+SE93REC) I