similar to: Extrapolating values from a glm fit

Buenas tardes, desde Uruguay, quiero realizar una regresión logística,con la función GLM, pero ademas quiero designarle a las observaciones clusters. La idea es decirle al programa que las observaciones corresponden a diferentes clusters. Saludos! Sebastián. [[alternative HTML version deleted]]

Dear All, probably a simple enough solution but don;t seem to be able to get my head around it...example based on a publicly available data set: mydata <- read.csv("https://stats.idre.ucla.edu/stat/data/binary.csv") mylogit <- glm(admit ~ gre + gpa + rank, data = mydata, family = "binomial") library(effects) plot(allEffects(mylogit) ? ?

Gracias a todos por sus respuestas, perdón si no fui muy claro. Lo que intento replicar es un análisis realizado en Stata, tengo que hacer los mismos cálculos pero en el r. En Stata lo que se hizo fue: xi: logistic i.coord i.v11_sexo, vce (cluster red) *Vce (cluster clustvar) especifica que los errores estándar permiten la correlación intragrupo, relajando el requisito habitual de que las

I have a data matrix with genes as columns and samples as rows. I want to create all possible gene ratios.Is there an elegant and fast way to do it in R and write it to a dataframe? Thanks for any help. Som. -- View this message in context: http://r.789695.n4.nabble.com/Calculating-all-possible-ratios-tp4627405.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML

I apologize that I've asked a similar question before, but being new to R I don't think I did a very good job of formating the question. I've included a text file since the date set is somewhat large. What I have is a huge string of numbers in a text file. The numbers are all separated by comma's and the groups are separated by a semicolon. What I would like to do is read each

I have a rather large data set (about 30 predictor variables) I need to preform a logistic regression on this data. My response variable is binary. My code looks like this: mylogit <- glm(Enrolled ~ A + B + C + ... + EE, data = data, family = binomial(link="logit")) with A,B,C, ... as my predictor variables. Some categorical, some continuous, some binary. I run the code and get

I realize this may be more of a math question. I have the following optim: optim(c(0.0,1.0),logis.op,x=d1_all$SOA,y=as.numeric(md1[,i])) which uses the following function: logis.op <- function(p,x,y) { ypred <- 1.0 / (1.0 + exp((p[1] - x) / p[2])); res <- sum((y-ypred)^2) return(res) } I would like to add weights to the optim. Do I have to alter the logis.op function by

Hi, I would like to plot time against rainfall data (data is at the end) using xyplot. The basic code looks like this: xyplot(rainfall~time, type="a") When I do this, the graph looks ok except that the x-axis has too many values. I would just like to display the years and not the months on the x-axis. I've been fiddling around with 'scales', and read previous posts about

I have survey data that I am working on. I need to make some multi-way tables and regression analyses on the data. After attaching the data, this is the code I use for tables for four variables (sweight is the weight variable): > a <- xtabs(sweight~research.area + gender + a2n2 + age) > tmp <- ftable(a) Is this correct? I don't think I need to use the strata and cluster

Hi, Included is an R.script that came from a much large date set being read in to R from a .txt file. Why is it that the first line codes with an error, but the second line works fine? Is there some line length limit in R? This happens at random places all through my data. Any help would be appreciated. -------------------------------------------------------------------- Bill Wyatt

I''m trying to figure out the best way (and hopefully leanest) to conditionally have precision to a float number. Here''s what I''m doing... I have a float (which has a default precision of 1) so like 250.0 What I want to do is have the precision go to 0 if the value after the . is 0 = so 250.0 would show as 250, but 250.5 would show 250.5. Thoughts? Thanks.

Dear all, Are there any functions to convert decimals to fractions in R? I have the result: > summary(as.factor(complete.ID)) 0 0.0133333333333333 0.04 2256 488 230 0.0666666666666667 0.0933333333333333 0.106666666666667 2342 310 726 0.133333333333333

Merry Christmas to you all and best wishes! I ran into exactly the same problem as described. OS: FreeBSD 9.0-Rel UPS: Eaton E-Series NV 600H NUT: from Ports, nut-2.6.5_1 driver: blazer_usb I am sure the problem is not permission-related as it occurs even when the driver runs as root. My tested recipe for USB permissions is: 1. run usbconfig to find where the device is connected. In my case:

We got all rows by: library(XML) doc = htmlParse('http://www.statcan.gc.ca/daily-quotidien/090520/t090520b1-eng.htm') rows = xpathSApply(doc, '//table/tbody/tr') The last row is: row_last = rows[15] row_last [[1]] <tr><td id="t1stub17" class="stub1 RGBShade"><b>Unsmoothed composite leading indicator</b></td>&#13; <td

The aggregate function for some reason will now work for me. The error I'm getting is: "Error in sort.list(y) : 'x' must be atomic for 'sort.list' Have you called 'sort' on a list?" agPriceList=aggregate(PriceList$Size, list(PriceList$bandNum),sum) *Price list dataframe:* dput(PriceList) structure(list(Price = c(0, 8.18, 8.27, 10.42, 10.5, 10.6, 11.13,

Hi, I am trying to do a lasso regression using the lars package with the following data (see attached): FastestTime WinPercentage PlacePercentage ShowPercentage BreakAverage FinishAverage Time7Average Time3Average Finish 116.90 0.14 0.14 0.29 4.43 3.29 117.56 117.77 5.00 116.23 0.29 0.43 0.14 6.14 2.14 116.84 116.80 2.00 116.41 0.00 0.14 0.29 5.71 3.71 117.24

Hi useRs, I am trying to calculate the Sharpe ratio with "sharpe" of the library "tseries". The documentation requires the univariate time series to be a portfolio's cumulated returns. In this case, the example given data(EuStockMarkets) dax <- log(EuStockMarkets[,"FTSE"]) is however not the cumulated returns but rather the daily returns of the FTSE

Hi, I have a matrix that I am displaying via image. I would like to obtain an image where the columns are 'grouped' (I have a grouping variable). But I am not sure how how I can draw the lines to indicate the grouping in the margin. I realize this is essentially waht heatmap does but as I have a set of custom breaks and colors I wanted to generate this via image. I can see that it is a

Hi All, I have the following dataset (triplicates values of 5 independent measurements and duplicate vaues of a control): 1 2 3 4 5 C 181.8 58.2 288.9 273.2 290.9 53.9 120.3 116.8 108.9 281.3 446 39.6 86.1 148.5 52.9 126 150.3 My aim was to find if mean values of Samples 1 - 5 are

Is there documentation on R limits? That is, max matrix size, etc.? Diagnostics when limits are exceeded are not always meaningful. For example: > x <- rep(0,50000*50000) Error in rep(0, 50000 * 50000) : invalid 'times' argument In addition: Warning message: In as.vector(data) : NAs introduced by coercion Here's another example: > library(orthopolynom) > hermite <-