similar to: getting the p-value from lm as a list object

Hi, perhaps this question was answered previously however I could not find them. My problem is how how to extract a particular statistic from the result given by lm(). For e.g. ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14) trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69) group <- gl(2,10,20, labels=c("Ctl","Trt")) weight <- c(ctl, trt) >

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

I would like to call both p-values and R-squared values from lm's in a function. I can get the p-values from coef(summary(name.lm))[r,c], however, I cannot figure out how to call the R-squared values without manually calling the summary and inserting them in the script - which negates the value of automating the process through a function. Thanks, Mike [[alternative HTML version deleted]]

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,

OK, what is the trick to extracting the overall p value from an lm object? It shows up in the summary(lm(model)) output but I can't seem to extract it: > test2 = apply(aa, 1, function(x) summary(lm(x[,1] ~ 0 + x[,3] + x[,6]))) > test2[[1]] Call: lm(formula = x[, 1] ~ 0 + x[, 3] + x[, 6]) [omitted summary output] F-statistic: 40.94 on 2 and 7 DF, p-value: 0.0001371 It does not seem

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|)

Hi, A frequently seen issue with importing SPSS data files, is that R does not import the 'long variable names'. I built a patch on the R-project's foreign module, in order to import the 'long variable names' from SPSS (record 7, subtype 13). To complete the job, I had to expand the "struct variable" definition to have 64 +1 charachters. I'm not aware of side

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) {

Quantreg package allows to plot the summary of models derived by quantile regression at different taus. The plot shows the parameters variation by varying taus: intercept and slope (for a linear model). Together with these values even confidence intervals may be plotted, based on the threshold given within the summary (e.g. alpha=0.01 equals 99% CI). However the graphic even plots the mean of

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 ~

Hi, I have some data that have this behaviour: | |******* | * | * | * | * |---------------- What is the best and simpler way to fit this in R? Thanks Ronaldo -- Ela pilotava um Continenal 2001 com igni????o autom??tica Magiclic... -- |> // | \\ [***********************************] | ( ?? ?? ) [Ronaldo Reis J??nior ] |>

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

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

Dear useRs, i have vectors of about 27 descriptors, each having 703 elements. what i want to do is the following 1. i want to do regression analysis of these 27 vectors individually, against a dependent vector, say B, having same number of elements.2. i would like to know best 10 regression results, if i do regression analysis of dependent vector against the random combination of any 4

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,

a1 is the first key in input. second column is x-axis and 3rd is y-axis and 4th is its corresponding key. Now for every key in 1st column I would like to calculate LR that gives p value. I tried to manage with a single key. But my problem is that How could I manage multiple keys in input. Thanx in advance input a1 1 2.5 x a1 2 3.5 x a1 3 4.5 x a1 1 2.6 x a1 2 3.8 x b1 1 4.6 y

Hello I am trying to get out of an lm model the fstatistics, however after I run the model I write > names(Model) and the fstatistic does not appear only these. names(Model) [1] "coefficients" "residuals" "effects" "rank" "fitted.values" [6] "assign" "qr" "df.residual"

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

Hi everyone, i've been trying to make a special plot with ggplot2, but I can't get it to fill the polygon I'd like to see filled so very very much. I want to display the difference or change in the distribution of the modified Rankin Scale between two groups. mRS is a scale for disability or daily activities competence. It looks like this.

[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],