search for: coefficeints

Dear all, I am using different multiple regression models (OLS and principal component regression (PCR)) to make prediction of my test set. And those models come from the same training set, except that the number of variables or descriptors (columns of X) used in OLS is less than those used in PCR. And I use square correlation coefficient (r^2) and root mean square to see the relationship

...182, 140, 157, 146, 182); sbp <- c(105, 121, 128, 149, 132, 103, 97, 128, 114, 129); case <- c(1, 3, 3, 2, 1, 2, 3, 1, 2, 2); result <- multinom(case ~ choles + sbp + choles:sbp, abstol=1.0e-20, reltol=1.0e-20, MaxNWts=10000); However, the estimated coeffcients and standard errors of the coefficeints are different from the SPSS. For instance, the estimated coefficients of the variable "choles" are 0.1946555 and 0.6244513 from the above result, but the SPSS result are 0.213120 and 0.662575. Standard errors are much more different. Why these kind of discrepancies occur? I'll b...

How can I get the p values from a glm ? I want to get the p values so I can add them to a custom report fitwean<- glm(data[,"JWean"]~data[,"Group"],data=data,family=binomial(link ="logit")) summary(fitwean) # This lists the coefficeints, SEs, z and p values, but I can't isolate the pvalues. names(summary(fitwean)) # I see the coefficients, but not the p values names(fitmens) # p values are not found here. Thank you! John John David Sorkin M.D., Ph.D. Professor of Medicine Chief, Biostatistics and Inform...

...from a glm ? I want to get the p values so I >> can add them to a custom report >> >> >> fitwean<- >> glm(data[,"JWean"]~data[,"Group"],data=data,family=binomial(link ="logit")) >> summary(fitwean) # This lists the coefficeints, SEs, z and p >> values, but I can't isolate the pvalues. >> names(summary(fitwean)) # I see the coefficients, but not the p values >> names(fitmens) # p values are not found here. > > Doesn't summary(fitwean) give a matrix? Then it's > c...

R 2.8.1 windows XP I am trying to learn how to use the boot function to perform a bootstrap of a regression. I have written a short trial program, shown below. Clearly I have done something wrong as the output of each of the 100 bootstrap values for the regression are exactly the same - there does not appear to be any bootstrap respampling!. What have I done wrong? # Define function to be run.

...How can I get the p values from a glm ? I want to get the p values so I can add them to a custom report > > > fitwean<- glm(data[,"JWean"]~data[,"Group"],data=data,family=binomial(link ="logit")) > summary(fitwean) # This lists the coefficeints, SEs, z and p values, but I can't isolate the pvalues. > names(summary(fitwean)) # I see the coefficients, but not the p values > names(fitmens) # p values are not found here. Doesn't summary(fitwean) give a matrix? Then it's colnames(summary(fitwean)$co...

...the p values so I >>> can add them to a custom report >>> >>> >>> fitwean<- >>> glm(data[,"JWean"]~data[,"Group"],data=data,family=binomial(link ="logit")) >>> summary(fitwean) # This lists the coefficeints, SEs, z and p >>> values, but I can't isolate the pvalues. >>> names(summary(fitwean)) # I see the coefficients, but not the p values >>> names(fitmens) # p values are not found here. >> >> Doesn't summary(fitwean) give a matrix...

...Sent: Wednesday, August 16, 2006 7:14 AM > To: Doran, Harold > Cc: r-help at stat.math.ethz.ch > Subject: [SPAM] - RE: [R] REML with random slopes and random > intercepts giving strange results - Bayesian Filter detected spam > > Hi again, > Even stranger is the fact that the coefficeints (the slope) > and the intercepts are not independent, in fact they are > directly inversely proportional (r squared = 1). > This means that that there isnt a random slope and intercept > for each individual (which is what I wanted), but straight > line that pivots in the middle a...

...the p values so I >>> can add them to a custom report >>> >>> >>> fitwean<- >>> glm(data[,"JWean"]~data[,"Group"],data=data,family=binomial(link ="logit")) >>> summary(fitwean) # This lists the coefficeints, SEs, z and p >>> values, but I can't isolate the pvalues. >>> names(summary(fitwean)) # I see the coefficients, but not the p values >>> names(fitmens) # p values are not found here. >> >> Doesn't summary(fitwean) give a matrix...

Hi R Gurus! I conducted regression and anova followings : Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 6.07e-01 5.95e-02 10.19 < 2e-16 *** nemp 2.87e-06 1.04e-07 27.63 < 2e-16 *** as.factor(corridor1)A -8.81e-02 2.13e-02 -4.14 3.6e-05 *** as.factor(corridor1)B

...4 PM, John Sorkin wrote: How can I get the p values from a glm ? I want to get the p values so I can add them to a custom report fitwean<- glm(data[,"JWean"]~data[,"Group"],data=data,family=binomial(link ="logit")) summary(fitwean) # This lists the coefficeints, SEs, z and p values, but I can't isolate the pvalues. names(summary(fitwean)) # I see the coefficients, but not the p values names(fitmens) # p values are not found here. Doesn't summary(fitwean) give a matrix? Then it's colnames(summary(fitwean)$coefficients) yo...

...gt;>> can add them to a custom report >>>> >>>> >>>> fitwean<- >>>> glm(data[,"JWean"]~data[,"Group"],data=data,family=binomial(link ="logit")) >>>> summary(fitwean) # This lists the coefficeints, SEs, z and p >>>> values, but I can't isolate the pvalues. >>>> names(summary(fitwean)) # I see the coefficients, but not the p values >>>> names(fitmens) # p values are not found here. >>> >>> Doesn't summary(fit...

...n a "normal" regression > indicates a non-zero intercet, forcing the regression line to have a > zero intercept changes the meaning of the regression coefficients. If > for some reason you want to have a zero intercept, but do not want to > change the meaning of the regression coefficeints, i.e. you still what > to minimize the sum of the square deviations from the BLUE (Best > Leastsquares Unibiased Estimator) of the regression, you can center your > dependent and indepdent variables re-run the regression. Centering means > subtracting the mean of each variable from the...

Hello, I wanted to create a histogram, but somehow I got stuck... The interval limits are: x = 1, 2, 3, 3.5, 4.5, 5, 5.5 The interval widths are therefore: 1, 1, 0.5, 1, 0.5, 0.5 Nothing I tried worked... Can anyone help me please? Thanks Tobias -- View this message in context: http://www.nabble.com/Histogram-tf4315900.html#a12288850 Sent from the R help mailing list archive at Nabble.com.

#I am trying to understand how R fits models for contrasts in a #simple one-way anova. This is an example, I am not stupid enough to want #to simultaneously apply all of these contrasts to real data. With a few #exceptions, the tests that I would compute by hand (or by other software) #will give the same t or F statistics. It is the contrast estimates that R produces #that I can't seem to