similar to: extracting P values from lm model

Dear R users, I am trying to draw error bars in a bar plot, I use this code (tried many others which did not work): install.packages() library(gplots) y <-c(39.02, 46.42) se <- c(7.57,7.35) plot <- barplot(y, beside=TRUE, col=0, ylim=c(0,47), axis.lty=1, main="far-red", xlab="latitude", names.arg=c("56N", "68N")) superpose.eb(plot, y, se,

Dear R users I have run an regression and want to extract the p value of the F statistics, but I can find a way to do that. x<-summary(lm(log(RV2)~log(IV.m),data=b)) Call: lm(formula = log(RV2) ~ log(IV.m), data = b[[11]]) Residuals: Min 1Q Median 3Q Max -0.26511 -0.09718 -0.01326 0.11095 0.29777 Coefficients: Estimate Std. Error t value Pr(>|t|)

Hello I have a data set summarized like this: File name= Height Group Ind Age Trait 1 1 1 20 1 1 2 21 1 2 1 22 1 2 2 21 1 3 1 24 1 3 2 45 1 4 1 23 1 4 2 26 2 1 1 45 2 1 2 12 2 2 1 25 2 2 2 26 2 3 1 45 2 3 2 43 2 4 1 23 2 4 2 47 . . . I would like to plot Trait ~ Age but a different plot for each Group. I tried: > plot(Height$Trait ~ Height$Age | Group) But does not work. Any

Dear Sir or Madam, I am a student at MSc Probability and Finance at Paris 6 University/ Ecole Polytechnique. I am using R and I can't find an answer to the following question. I will be very thankful if you can answer it. I have two vectors rendements_CAC40 and rendements_AlcatelLucent. I use the lm function as follows, and then the sumarry function: regression=lm(rendements_CAC40 ~

I'd like to automatically plot the p-value and r^2 of a linear model. I know that I can extract r^2 with foo <- lm(y~x) a <- summary(foo) a$r.squared I can't find any similar functionality to obtain the p-value based on the ftest a$fstatistic returns the actual f-test and df, but not the p-value. Any thoughts? Thanks, Adam using R-0.65.1 Win32

Dear list, I want to retrieve the p-value of a two-polynomial regression. For a one-polynomial lm I can easily do this with: summary(lm(b~a, data=c)[[4]][[8]]. But how do I find the final p-value in the two-polynomial regression? Under $coefficients I don't find it Any suggestions? Patrick alt <-(2260,2183,2189,1930,2435, 2000,2100,2050,2020,2470, 1700,2310,2090,1560,2060,

Hi everyone, I'm trying to determine the significance of a trendline. From my internet search months ago, I came across the following post. I modified tim and dat for simiplicity. tim <- 1:10 dat <- c(0.17, 1.09 ,0.11, 0.82, 0.23, 0.38 ,2.47 ,0.41 ,0.75, 1.44) fstat <- summary(lm(dat~tim))$fstatistic p.val <-

Hi all, I'm struggling with nls. How do you know if your model is significant? For a lm, you get a p-value, but you don't get it for a nls. Is there a way to calculate it? For a lm I use this: a<-summary(lm(model ~obs)) f.stat<-a$fstatistic p.value<-1-pf(f.stat["value"],f.stat["numdf"],f.stat["dendf"]) Is there something similar for a nls?

could someone explain why the name of FPVAL gets " .value" concatenated onto it when the code below is run and temp is returned. I've been trying to figure this out for too long. It doesn't matter when I put the FPVAL in the return statement. It happens regardless of whether it's first or last. Thanks. f.lmmultenhanced <- function(response, pred1, pred2) {

Hi, I'm trying to get the p-value from the 'lm' regression function as a list object. For example, I can get r^2 from the following code by entering summary(fm)$r.squared. Is there a way to get the p-value? If not, is there a function where I can enter the f-value and degrees of freedom to get the p-value? Thanks. x <- c(1,2,3,4,5,6,7,8,9,10) y <- c(1,2,3,4,4,5,6,8,1,9) fm

Hi there, I tried it many times but didn't get it worked. I just want to export the summary of a OLS regression (lm() function) into a csv-file including the "call"-formula", "coefficients", "r-squared", " adjusted r-squared" and "f statistic". I know I can export: write.csv2(Regression_60d_ann$coefficients,

inputfille snpid indid genotype gvariable probeid gene geneexpression rs1040480 CHB_NA18524 C/T 2 GI_19743926-I PTPRT 5.850586 rs1040480 CHB_NA18526 C/C 1 GI_19743926-I PTPRT 6.028641 rs1040480 CHB_NA18529 C/C 3 GI_19743926-I PTPRT 5.944392 rs1040481 CHB_NA18532 C/C 1 GI_19743926-I PTPRT 5.938578 rs1040481 CHB_NA18537 C/C 2 GI_19743926-I PTPRT 5.874439 rs1040481 CHB_NA18540 C/C 3 GI_19743926-I

Just to inform: I posted that before in R-sig-ecology but as it might be interesting also for other useRs, I post it also to the general r-user list: Hello Alexandre, thank you very much. I also found another way to extract summarizing information from lm results over e.g. 1000 repeated model runs: results2 <- t(as.data.frame(results)) summary(results2) Although some questions popped up in

Dear all, I am not fluent in R and am struggling to 1) apply a lm to a weight-size dataset, thus the model has to run separately for each species, each year; 2) extract coefs, r-squared, n, etc. The data look like this: year sps cm w 2009 50 16 22 2009 50 17 42 2009 50 18 45 2009 51 15 45 2009 51 16 53 2009 51 17 73 2010 50 15 22 2010 50 16 41 2010 50 16 21 2010

Hi I have 1800 response variables to regress on two factors (latitude and age), what is the script to run all response variables at once instead of writing 1800 models? Thanks R. ________________________________________ L?hett?j?: r-help-bounces at r-project.org [r-help-bounces at r-project.org] k&#228;ytt&#228;j&#228;n Dennis Murphy [djmuser at gmail.com] puolesta L?hetetty: 25.

Jon, I need to create a database of basics blocks and their execution time. The only thing I'm concerned is if a block A is more expensive than a block B. Do you think that even with the overhead I would be able to get the A > B information? Like: overhead + time(A) > overhead + time(B) => A > B. If so, I'm not too much concerned about the accuracy. Not sure if I was clear,

[Please use the subject line!] In the help page for summary.lm, the "Value" section says that the returned object has a component called "fstatistic", which has the F-statistic and the associated numerator and denominator degrees of freedom. You can get the p-value by something like: fstat <- summary(speciallinearmodel)$fstatistic pval <- pf(fstat[1], fstat[2],

Hello I am able to extract partial regression coefficients from a fitted model object "model", i.e. model <- lm(var.sel.gkm, weights = count.gkm, data = DATA) summary(model) write.table(model$coef, file = "C:/coef_CO_gkm.txt", row.names = TRUE, col.names = TRUE) I was wondering if anyone could advise me how to extract other object items such as std. error, t-values

Hello I have a data set with outlier and it is not normally distributed. I would instead like to use a more robust distribution like t-distribution. My question is if the coefficients of the regression are different from zero, but assuming a t-distribution. Could someone hint me what package to use or.... Thanks in advance Rosario

Hi, I want to generate an histogram and plot on the y axis the percentage of a categorical variable and on the x axis a nominal variable. I want to move the origin to have 2 categories below 0. Hope somebody could help me. Thanks. Best, -- Rosario Ivano Scandurra [[alternative HTML version deleted]]