similar to: Definition of t-value

Dear R-Helpers, I want to compare the results of outputs from glmmPQL and lmer analyses. I could do this if I could extract the coefficients and standard errors from the summaries of the lmer models. This is easy to do for the glmmPQL summaries, using > glmm.fit <- try(glmmPQL(score ~ x*type, random = ~ 1 | subject, data = df, family = binomial), TRUE) > summary(glmmPQL.fit)$tTable

Hello, I would like to fit a linear regression and when I use summary(), I got the following result: Call: lm(formula = weight ~ group - 1) Residuals: Min 1Q Median 3Q Max -1.0710 -0.4938 0.0685 0.2462 1.3690 Coefficients: Estimate Std. Error t value Pr(>|t|) groupCtl 5.0320 0.2202 22.85 9.55e-15 *** groupTrt 4.6610 0.2202 21.16 3.62e-14

Hello R users, I have a substantial question about statistics, not about R itself, but I would love to have an answer from an R user, in form of an example in R syntax. I have spent whole Sunday searching in Google and browsing the books. I've been really close to the answer but there are at least three standard errors you can talk about in the linear regression and I'm really confused.

Hi, How can I extract the standard deviation of the coefficients when using the lm function. I know ____$coefficient gives me the individual betas. thank you --------------------------------- [[alternative HTML version deleted]]

Hi all, In assessing the concordance of two sets of ANOVA results, I would like to extract the p values from the summaries. I had a look at previous answers to this problem, and the suggestions do not seem to work: # toy example test.df<-data.frame(subno=c(1:50,1:50), ndrinks=c(rpois(50,4.5),rpois(50,4)), b4after=c(rep(1,50),rep(-1,50)))

Dear R-helpers, I would like to do a Spearman rank order test, and used the cor() function with the method "spearman". It gives me a number (correlation coefficient?) , but how can I get the p-value? Thank you for the help in advance! Regards, Anne-Katrin -- [[alternative HTML version deleted]]

Hi all! I try to estimate a statistic of the form: (x1-x2)/(y1-y2), where x1,x2,y1,y2 represent variable means, so each has an estimate and standard error associated with it. How is it possible to estimate the mean and the variance of this ratio? Thank you! [[alternative HTML version deleted]]

Hi I have the following formula (I hope it is clear - if no, I can try to do better the next time) h(x, a, b) = integral(0 to pi/2) ( ( integral(D/sin(alpha) to Inf) ( ( f(x, a, b) ) dx ) dalpha ) and I want to do an mle with it. I know how to use mle() and I also know about integrate(). My problem is to give the parameter values a and b to the

Hi, on a > summary(lm(y~x)) are the computed t-values for two.sided or one.sided. By looking on some tables they seem like they are for two.sided. Is it possible to have them for one.sided? If this makes sense... Thanks. [[alternative HTML version deleted]]

Hi all I am hoping this is just a minor problem, I am trying to implement a best subsets regression procedure on some ecological datasets using the regsubsets function in the leaps package. The dataset contains 43 predictor variables plus the response (logcount) all in a dataframe called environment. I am implementing it as follows: library(leaps)

Hi, I am an R beginner and having problems structuring my REML models. I have a model with y=weight x1=time x2=timesquared id=individual identity I need to structure the model such that in the random effects there is a constant intercept for all individuals but a separate individual slope for both x1 and x2 (a coefficient score for every individual).

Hi I have two symmetrical distance matrices and want to compute the correlation coefficient between them (after turning them into vectors). Is there a way of selecting only the upper triangular part of each matrix, then convert this into a vector so I can compute the correlation? Many Thanks Eleni Rapsomaniki

Hello: I want to use values from the output of linear models done using permuted data to construct a random distribution. The problem I am having is the extraction of a value, say the p-value or the regression coefficient, from the summary of a linear model. When summarizing a linear model I get this: Call: lm(formula = fitness ~ mm) Residuals: Min 1Q Median 3Q Max

Hello R helpers, I am trying to do a linear OLS regression of y on two variables x1 and x2. I want to constrain the coefficients of x1 and x2 to sum up to 1. and therefore run a constrained OLS. Can anybody help with this? (I have seen some answers to similar questions but it was not clear to me what I need to do) - I have tried the lm function with offset but I must not have used it properly.

I want to organize outputs from several regressions into a handy table. When I try the following, each of my "fit_s" is replaces instead of read. Is there a way to read from the regression summaries that does not require writing separate lines of code for each? -Ben Osborne > fit1<-lm(dBA.spp16$sp2.dBA.ha~dBA.spp16$sp1.dBA.ha) >

Dear R Help, I have been struggling with this problem without making much headway. I am attempting to avoid using a loop, and would appreciate any suggestions you may have. I am not well versed in R and apologize in advance if I have missed something obvious. I have a data set with multiple sites along a river where metal concentrations were measured. Three sites are located upstream of a mine

Dear R-users, I am wondering whether R implements a function returning the non central parameter of a t distribution (equivalent of the TnoncT function from SAS), given /x/ a value from a t distribution, /df /the degrees of freedom and /p/ the probability of x under this distribution. Thanks a lot, Matthieu -- Matthieu Dubois, /Ph.D/. /Student/ Cognitive Neuroscience Unit, UCL,

Thanks Dimitris!!! That's much clearer now. Still have a lot of work to do this weekend to understand every bit but your code will prove very useful. Cheers, Aziz -----Original Message----- From: Dimitrios Rizopoulos [mailto:Dimitris.Rizopoulos at med.kuleuven.be] Sent: May 12, 2006 4:35 PM To: Chaouch, Aziz Subject: RE: [R] Maximum likelihood estimate of bivariate

Hi All: I would like to generate a binomial random variable that correlates with a normal random variables with a specified correlation. Off course, the correlation coefficient would not be same at each run because of randomness. I greatly appreciate your input. Ashraf

Hi For bureaucratic reasons beyond my control I need to rewrite an R function (for producing operating characteristic curves) as an Splus function ( version 6 , windows XP ). The R function makes extensive use of the fact that the student's t distribution function pt() has a non-centrality parameter built in ... sadly that parameter is not present in the Splus pt() function .