similar to: multinormial runs tests?

Hello, I have a set of data that has a Date column looks like this: 12/9/2007 12/16/2007 1/1/2008 1/3/2008 1/12/2008 etc. I'd like the date to look something like the follow (so that I could sort by date easily). 20071209 20071216 20080101 20080103 20080112 How to do it? Thank you very much Julia -- View this message in context:

Hello, I have a data set that looks like this. ID value 111 5 111 6 111 2 178 7 178 3 138 3 138 8 138 7 138 6 . . . I'd like to calculate the mean and var for each object identified by the ID. I can in theory just loop through the whole thing..., but is there a easier way/command which let me calculate the mean/var by ID? Thanks, Julia -- View this

Dear R users, I am building a hierarchical model on a large data set. It can take quite some time to finish one fit, I was just wondering whether it is possible to store the fit object (the result) to a file for later (offline) analysis. thanks Julia -- View this message in context: http://www.nabble.com/how-to-store-lme-lmer-fit-result-tp19910951p19910951.html Sent from the R help mailing

Hello, I have a data file (.csv) that has a size of about 2.6 GB. I am not able to read in the whole data set because of the memory limit. I actually only need some columns (3 columns) of the data set, is there a way to read in specified columns? I am using windows. Thanks, Julia -- View this message in context:

Hello, I have a vector: x <- c("A", "A", "A", "B", "A", "A", "C") I'd like to compare each of elements of vector x from its previous element (except for the 1st element which does not have previous element). So I'd like to get a vector y (of same length) that looks something like (0, 0, 0, 1, 1, 0, 1) or (F, F, F,

Dear R users: I have a data set that looks something like this: ID time y 1 2/01/2008 4 1 2/09/2008 12 1 9/01/2008 8 2 1/06/2008 3 2 3/01/2008 4 2 3/09/2008 9 2 6/03/2008 4 3 1/02/2008 3 3 1/10/2008 8 3 2/02/2008 7 3 2/10/2008 3 I'd like to sum up the weekly data to the monthly level, so that it looks something

Dear R users, I need to compare two scatter plots, plot(x1, y1) plot(x2, y2) and would like to plot them in the same figure. How do I do it? Thank you. -- View this message in context: http://www.nabble.com/two-scatter-plots-in-one-tp21963375p21963375.html Sent from the R help mailing list archive at Nabble.com.

Hello, I have a time series plot drawn using 3 different colored lines, each line corresponds to different category group. I'd like to put legends on the plot. I am using "legend" to do this, however, I can either specify lty or col in legend. Will I be able to do the following in the legend box: a solid black line then g1, a solid red line then g2, a solid blue line then g3?

Dear R users: I am running lmer(), and I had the following warning message: "In mer_finalize(ans): iteration limit reached without convergence (9) What is the default limit for lmer()? And how do I increase the limit? Many thanks, Julia -- View this message in context: http://www.nabble.com/How-to-increase-iteration-limit-for-lmer%28%29--tp20252974p20252974.html Sent from the R help

Hello R-User! I appologise in advance if this should also go into statistics but I am presently puzzled. I have a data.frame (about 300 rows and about 80 variables) and my variables are dichotomous factors, continuous (numerical) and ordered factors. I would like to calculate the linear correlation between every pair of my variables, because I would like to perform a logistic regression (glm())

Dear community I'm pretty new to R and I'm trying to do a Point-baserial correlation for a nominal dichotomous variable with a interval scaled variable. It works fine, but the output just shows me the correlation and nothing else (p-Value would be important). I tried it with the following codes: - biseral.cor() - cor.biseral() - I also tried a polyserial() I've found on this

I am trying to run a GLMM on some binomial data. My fixed factors include 2 dichotomous variables, day, and distance. When I run the model: modelA<-glmmPQL(Leaving~Trial*Day*Dist,random=~1|Indiv,family="binomial") I get the error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 >From looking at previous help

Hello, I am running polychoric correlations on a dataset composed of 12 ordinal and binary variables (N =384), using the polycor package. One of the association (between 2 dichotomous variables) is very high using the 2-step estimate (0.933 when polychoric run only between the two variables; but 0.801 when polychoric run on the 12 variables). The same correlation run with ML estimate returns a

Dear R-sians.. I am trying to plot boxplots with side-by-side option.. I tried some of the posted suggestions and could not make it work due to unequal sizes of categories... e.g. weekly measured water depth values are categorized into 5 levels based on their values such measurement is again categorized into dichotomous levels - based on the result of a test I would like generate boxplot of

Hi everyone, Have sample of items for each one, a set of 20 dichotomous (absent-present) variables are expressed. I'm trying to understand how to explore the co-occurence of each variable. Read some papers concerning smallest space analysis, but it does not seems implemented in any R package (and my protamming skills are =0). Non metric MDS gives error messages, probably because of the

Dear R users: I have a continuous outcome variable and four predictors, two continuous and two dichotomous. i would like to use the lattice plot to create scatter plots for the continuous predictors and boxplots for the dichotomous predictors. with 4 continuous variables, this is what i have been doing: trial = rbind ( cbind ( cimt$ant.mean, cimt$age, 1 ), cbind ( cimt$ant.mean, cimt$sbp, 2 ),

I'd like to estimate an ordinal logistic regression with a random effect for a grouping variable. I do not find a pre-packaged algorithm for this. I've found methods glmmML (package: glmmML) and lmer (package: lme4) both work fine with dichotomous dependent variables. I'd like a model similar to polr (package: MASS) or lrm (package: Design) that allows random effects. I was

Hello R people, I am looking to pay someone to help write some R code. Inputs: Study identifier: ID Number for the study, each ID number is for one study only each block set should only be used for that study. This will require that you store the results from the blocks someplace on the file system. Trait #1: dichotomous rural / urban Trait #2: dichotomous sick / healthy Assignment Ratio:

Is it possible to fit a structural equation model with link functions in R? I am trying to build a logistic-regression-like model in sem, because incorporating the dichotomous variables linearly seems inappropriate. Mplus can do something similar by specifying a 'link' parameter, but I would like to be able to do it in R, ofcourse. I have explored the 'sem' package from John Fox,

Dear People at R help, I am trying to figure out the syntax for a three-level logistic model with a single random effect (intercept): Data Collected My data consist of three levels: level 1 is four setting for each student (setting nested within student), and each student is registered in one of 14 universities (students nested within university). More detailed: A. 2,479 students who have a