similar to: Homogeneity of regression slopes

Hi, I'm trying to get confidence intervals to slopes from a linear model and I can't figure out how to get at them. As a cut 'n' paste example: ################# # dummy dataset - regression data for 3 treatments, each treatment with different (normal) variance x <- rep(1:10, length=30) y <- 10 - (rep(c(0.2,0.5,0.8), each=10)*x)+c(rnorm(10, sd=0.1), rnorm(10,

Hi All, I am confused with SMATR's test for common slope. My null hypothesis here is that all slopes are parallel (common slopes?), right? So if I get a p value < 0.05 means that we can have confidence to reject it? That slopes are different? Or the other way around? it means that we have statistical confidence that the slopes are parallel? thanks -- Eugenio Larios PhD Student University

Hi I have (8 measures * 96 groups) = 768 datasets for which I did linear regressions using lm(). Now I want to compare the slopes for each of the 8 measures in each of the 96 groups. As I understand , I can not use > anova(lm1, ..., lm8) as the lm1 ... lm8 are based on different datasets. I also read in previous discussions in this list, that I can see if the slope +- stddev(slope)

Hello, I was wondering if anyone could please help me with some simple questions regarding ANCOVA and the assumption of homogeneity of slopes. The standard design of ANCOVA assumes the homogeneity of regression coefficients of the different groups. This assumption can be tested using the factor ?? covariate interaction, which should subsequently be removed. However if this assumption is not

Not really r-specific: Z = (b1 - b2) / SQRT ( SEb1^2 + SEb2^2) -------Original Message------- From: Gijsbert Stoet <stoet at volition.wustl.edu> Sent: 07/20/03 09:51 PM To: r-help at stat.math.ethz.ch Subject: [R] how to test whether two slopes are sign. different? > > Hi, suppose I do want to test whether the slopes (e.g. determined with lsfit) of two different population are

Hi, How would one go about determining if the slope terms from an analysis of covariance model are different from eachother? Based on the example from MASS: library(MASS) # parallel slope model l.para <- lm(Temp ~ Gas + Insul, data=whiteside) # multiple slope model l.mult <- lm(Temp ~ Insul/Gas -1, data=whiteside) # compare nested models: anova(l.para, l.mult) Analysis of Variance

Hi I want to extract the random slopes from a lmer (I am doing a random regression), but are the answers obtained from ranef or coef? My model is: mod1<-lmer(B~ A +(A|bird), family=quasibinomial) And I want to obtain a slope for each individual bird but am not sure which output I need and can't find the answer anywhere. Thanks Sam Dr Samantha Patrick EU INTERREG Post Doc Davy 618

Can you provide the summary(m2) results? > -----Original Message----- > From: Simon Pickett [mailto:S.Pickett at exeter.ac.uk] > 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,

Hi, I've made a research about how to compare two regression line slopes (of y versus x for 2 groups, "group" being a factor ) using R. I knew the method based on the following statement : t = (b1 - b2) / sb1,b2 where b1 and b2 are the two slope coefficients and sb1,b2 the pooled standard error of the slope (b) which can be calculated in R this way: > df1 <-

I am interested in whether the slopes in a linear model are different from 0. I.e. I would like to obtain the slope estimates, and their standard errors, ``relative to 0'' for each group, rather than relative to some baseline. Explicitly I would like to write/represent the model as y = a_i + b_i*x + E i = 1, ..., K, where x is a continuous variate and i indexes groups (levels of a

Hello R community, I have a question regarding correlation and regression analysis. I have two variables, x and y. Both have a standard deviation of 1; thus, correlation and slope from the linear regression (which also must have an intercept of zero) are equal. I want to probe two particular questions: 1) Is the slope significantly different from zero? This should be easy with the lm

Hi everyone, I'm a bit new here (and new to R), and I was trying to do an OLR, and testing the parallel slope assumption seems be very important. I browsed through past postings, and didn't find much to help me in this area. I was wondering if anyone knew how I could go about doing this. Thank you. -- View this message in context:

Hello, Is there any formula or way to compare slopes of different functions? If we fit 2 functions in our data, and we have 2 slope parameters, how can we compare these slopes? Plotting y=5x and y=exp(5x) in which slope is equal to 5 in both of them.. doesn't seem that it makes sense to compare them. Maybe what I ask is basic statistics.. but you may be aware of some formula that could

Hi all, I need to test the significnce of difference between slopes of two regression lines and regression line with theoretical line. I try to use Slope.test function from emu package, but an error occured... library(emu) d1<-data.frame(P1=c(1,2,3,5,7,8,9,13,14,15), P2=c(1,2,5,8,11,13,15,15,18,24), R=c(2,7,8,9,16,21,27,31,33,36)) # First data set m1<-lm(R~P1+P2+P1*P2,data=d1) # Regr.

Hi, all, I am thinking to compare a group of slopes from regression lines to see if they are different overall, and then make specific comparisons between groups. How can I achieve that in R? I searched the archives and there are only discussions about comparing two lines a time. Thanks. A sample data set is like the following. I would like to compare the regression slopes between the five

Hello, I have a linear model with different slopes for different treatment groups. I need to pairwise compare the different slope estimates for the different treatment groups. Is there a package that does pairwise comparisons of slope coefficients, making the appropriate adjustments in the P values? Thanks, John. -- ========================================== John Janmaat Department of

I have data from a design in which items are completely nested within subjects. Subject is the only second-level factor, but I have multiple first-level factors (IVs). Say there are 2 such independent variables that I am interested in. What is the proper syntax to fit a mixed-effects model with a by-subject random intercept, and by-subject random slopes for both the 2 IVs? I can

Hello, I've written a simple (although probably overly roundabout) function to test whether two regression slope coefficients from two linear models on independent data sets are significantly different. I'm a bit concerned, because when I test it on simulated data with different sample sizes and variances, the function seems to be extremely sensitive both of these. I am wondering if

Hello, I'm a newcomer to R so please forgive me if this is a silly question. It's that I have a linear regression: fm <- lm (x ~ y) and I want to test whether the slope of the regression is significantly less than 1. How can I do this in R? I'm also interested in comparing the slopes of two regressions: fm1 <- lm (x ~ y) fm2 <- lm (a ~ b) and asking if the slope of fm1 is

Dear list members, I am working with a multilevel growth curve, that in its simplest form goes like follows: Yit = Ai + Bi t + eit (the error term is assumed to follow an AR(1) autorregressive process) One major topic in my research is the convergence in the values of Y over time. Thus, I am interested in the relationship between the random effects for the intercept and the slope, and I