similar to: OLS standard errors

Hi, I hope somebody can help me with this issue: I am doing population pyramids using the barplot command, so in the left side I have male age structure and in the right side the female age structure. To plot the male age structure I put the data in negative numbers. Now, I want to change the sign in the bar plot in such way that I have no-sign numbers, both in left and right side of the graph. I

i have a series of regressions i need to run where everything is the same except for the dependent variable, e.g.: lm(y1 ~ x1+x2+x3+x4+x5, data=data) lm(y2 ~ x1+x2+x3+x4+x5, data=data) lm(y3 ~ x1+x2+x3+x4+x5, data=data) is it possible to run all these regs with a single command? given that the bulk of the work for linear regressions is inverting a matrix that depends only on the independent

Hi R people, I have a very basic question to ask - I'm sorry if it's been asked before, but I searched the archives and could not find an answer. All the examples I found were much more complicated/nuanced versions of the problem - my question is much more simple. I have data with multiple, nested fixed effects (as I understand it, fixed effects are specified by the experimental design

Hi all, I am quite sure it's not a bug, but I am going nuts about this. I do not possibly understand why I get different results for b1 and b2 as shown below. x=c(183,191,192,193,195,206,207,209,210,211,212,213,214,217,218,221,222,223, 224,225,227,228,229,230) y=c(221,225,228,241,242) z=y[y<max(x)] ##all Ys smaller than the maximum of X a=ifelse(length(z)==0,NA,max(z)) ##assign NA if

Hi, I have seen a discussion in the R-help asking whether nonparametric manova has been implemented in R yet. This discussion is form March 2006 and there seemed to be no package or function implemented at the time. Has this changed? Is there a package that provides nonparametric manova as in McArdle and Anderson (2001) and Anderson (2001) now? Thanks, Daniel ------------------------- cuncta

Hi, I am trying to extract some numbers from a text string. The problem is that the delimiting symbols are identical so that I do not know how to tell "sub" between which of them to extract. The string looks like this 12/01/03/08 The extracted variables should look like: x1=12 x2=01 x3=03 x4=08 If anybody could help or point me to useful help, I would be greatful. Cheers, Daniel

I have a matrix containing means and CIs (lower and upper in two columns, so three columns for every data point) for several points. I have to build a graph of these means accompained by the CIs (as wiskers). No problems with making the graph of means, but I don't know how to introduce CIs. Can anybody advise? -- View this message in context:

Accepted and forgotten. It just reminds us to check on our prejudices once in a while. Also, I realized that my description was not entirely accurate. You actually had to click the link on the page you posted to get this: http://www.odesk.com/jobs/College-Assistance_~~dd7622f6bdef9177 I am an MSc. computer science student in a foreign university! Need help to solve the exercises in the following

Hi everyone, I'm having some difficulty getting "simple effects" for the ols() function in the rms package. The example below illustrates my difficulty -- I'll be grateful for any help. #make up some data exD <- structure(list(Gender = structure(c(1L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L), .Label = c("F", "M"), class = "factor"),

Hi, I am trying to parse a large amount of text using gregexpr(). Unfortunately, I get an "input buffer overflow" message when I attempt that with too large an amount of text. The error messages occurs before the parsing. The problem is that I cannot assign the text to a variable (an object) if the text is too large. This problem has been mentioned before, which I found using the

#I have a data frame with a numeric and a character variable. x=c(1,2,3,2,0,2,-1,-2,-4) md=c(rep("Miller",3), rep("Richard",3),rep("Smith",3)) data1=data.frame(x,md) #I subset this data.frame in a way such that one level of the character variable does not appear in the new dataset. data2=data1[x>0,] data3=subset(data1,x>0) #However, when I check the levels

I am trying to plot an interaction in a multilevel model. Here is some sample data. In the following example, it is longitudinal (i.e., repeated measures), so the outcome, score (at each of the three time points), is nested within the individual. I am interested in the interaction between gender and happiness predicting score. id <- c(1,1,1,2,2,2,3,3,3) age <-

I am writing a rd doc, and need to use "#" in a url adress. This would make: \url{http://www.xxxx.org/myfolder/#myanchor} Of course, I suppose this will not work because # is a special character starting a comment line in the rd dialect. I did not found a similar example in "Writing R exentions". I am not sure bout using \dQuote{a quotation}), and use \sQuote and \dQuote

Hello, I'm trying to do cor(x1,x2) and I get the following error: Error in cor.default(x1, x2) : missing observations in cov/cor A few things: 1. I've used cor() many times and have never encountered this error. 2. length(x1) = length(x2) 3. is.numeric(x1) = is.numeric(x2) = TRUE 4. which(is.na(x1)) = which(is.na(x2)) = integer(0) {the same goes for is.nan()} 5. I also try

Dear list, I'd like to create a visual plot of a clmm() I've fitted using the 'ordinal' package in R. It's possible to do this with a glm() by using the 'effects' package. For example: library(effects) data(BEPS) mod <- lm(political.knowledge ~ age + gender + vote, data=BEPS) eff <- effect("age", mod, default.levels=100) plot(eff,

Hi everyone, I have an array with a variable called comments. I wish to count the number of subjects whose post-experiment comments contain a string x and then cross tab this with other variables of interest, ex. age. Does anyone have any suggestions on how to count unique occurrences of a string embedded within a variable and cross-tab it with other variables? I've looked through the help

Hi, I want to extract individual names from a single string that contains all names. My problem is not the extraction itself, but the looping over the extraction start and end points, which I try to realize with apply. #Say, I have a string with names. authors=c("Schleyer T, Spallek H, Butler BS, Subramanian S, Weiss D, Poythress ML, Rattanathikun P, Mueller G") #Since I only want the

Hi, using polynomial contrasts for the ordered factors in an experiment leads to much nicer covariance structure than using treatment contrasts. It is easy to assess the mean effect for each of the experimental groups. However, standard errors are provided only for the components of the orthogonal contrasts. I wonder how to assess the standard errors not of the components, but of the respective

Dear R users, I have a question about the plot with the package gam. I need to plot different main effect functions, related to different gam models, in the same graphics (i.e. the same covariate about different models). I used the plot.gam e preplot.gam documentations. Using preplot.gam I can plot the single function but I'm not able to put all the functions together. Does anybody can help

I have a data set like the following: subject visit x1 1 1 0.5 1 2 1.2 1 3 0.7 2 1 0.4 2 2 0.6 2 3 1.0 ..... where x1 is the interval between the two visits. Now I want to calculate the cumulative intervals since the beinging, for example subject visit x1 cum 1 1 0.5 0.5 1 2 1.2 0.5+1.2 1 3 0.7 0.5+1.2+0.7 2 1 0.4 0.4 2 2 0.6 0.4+0.6 2 3 1.0 0.4+0.6+1.0 ..... is there an easy to generate the