search for: estmate

Dear all, I have wrote a code for a linear regression. I want to write a loop for so, that I can get estimate for pavlues for six predictors. But I am getting for estmate for only last one. How can I get pvalues for all my predictors in a loop?? Anticipating your help Thanks Ales > mat<-matrix(rnorm(36),nrow=6) > mat [,1] [,2] [,3] [,4] [,5] [,6] [1,] 1.10536338 -0.7613770 -1.7100569 -1.8...

...ping variable. I would like know the correlation of Y with X (Y~X) and the effect of within subject variance on this correlation. And thus, overall significance and correlation. Will it be valid to fit lm to all combinations of x and y and take an average values of p and R-squared? Usually, I estmate the correlation using simple lm between outcome and averaged predictor (1-to-1, i.e. 20 outcomes versus 20 predictors). However, I would like to take in account variations associated with replicated measurements (i.e. the same 20 outcomes versus 20 predictors replicated say 3 times), and, therefore...

Dear R helpers, I need to estimate a probit model with box constraints placed on several of the model parameters. I have the following two questions: 1) How are the standard errors calclulated in glm (family=binomial(link="probit")? I ran a typical probit model using the glm probit link and the nlminb function with my own coding of the loglikehood, separately. As nlminb does not

Does anyone know where I can find a proof of the fact that when each X matrix in a SUR is the same, then SUR estimation is equivalent to OLS estmation. The proof is supposedly in William Greene's book but that book costs 157.00 an has mixed reviews so I am reluctant to purchase it. Thanks. -------------------------------------------------------- This is not an offer (or solicitation of an

Dear List I am trying to fit a simutaneous equation logit model. i.e., the response variables of the structured equations are binomial, I am not sure if systemfit can do this job. A google search doesn't yield too much helpful information. Your knowledge on any other packages or codes are appreciated. Thanks will

Hi, this is my first time using the nlme package, and I ran into the following puzzling problem. I estimated a mixed effects model using lme, once using groupedData, once explicitly stating the equations. I had the following outputs. All the coefficients were similar, but they're always slightly different, making me think that it's not due to numerical error. Also, what is the

Dear listers, I can't find the variance or se of the coefficients in a multilevel model using lme. I want to calculate a Chi square test statistics for the variability of the coefficients across levels. I have a simple 2-level problem, where I want to check weather a certain covariate varies across level 2 units. Pinheiro Bates suggest just looking at the intervals or doing a rather

Hello, I have found a problem with using the glm function with a gamma family. I have a vector of data, assumed to be generated by a gamma distribution. The parameters of this gamma distribution are estimated in two ways (i) using the glm() function, (ii) "by hand", using the optim() function. I find that the -2*likelihood at the maximum found by (i) is substantially larger than that