similar to: Error in structural equation model - "The model has negativedegrees of freedom"

Dear R-help list members, I forgot to copy my reply to the r-help list. Here's most of it. John -------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -------------------------------- -----Original Message----- From: John Fox [mailto:jfox at mcmaster.ca] Sent: Sunday,

Hi I am running a structural equation model with R using the sem command; am getting the following error: "Error in sem.default : The model has negative degrees of freedom = -4" My model is as follows: s_model = specify.model() x1->m1, b1,NA x2->m1, b2,NA x3->m2, b3,NA x4->m2, b4,NA x5->m2, b5,NA x6->m2, b6,NA m1->y, a1,NA m2->y, a2,NA m1<->m1, v1,NA

Hi all, I am attempting to learn my way through the sem package by constructing a simple structural model for some of my data on bird diversity, abundance, and primary productivity. I have constructed a covariance matrix between these variables as per the following: >S_matrix = matrix(c( >+ 0.003083259, 0, 0, >+ 0.143870284, 89.7648490, 0, >+ 0.276950919,

I want to get some "simple" logic regression examples to work before exploring a hard problem. I can get results, but I'm having some problems using "cat" to save the logic regression equation to a disk file. Consider this: # Simple Logic Regression Example # efg, 23 Feb 2005 library(LogicReg) # Create simulated data with known logic equation: # "noise"

I'm pasting below a working R file featuring a function I'd like to polish up. I'm teaching regression this semester and every time I come to something that is very difficult to explain in class, I try to simplify it by writing an R function (eventually into my package "rockchalk"). Students have a difficult time with predict and newdata objects, so right now I'm

Hi, I wonder if anyone can help me with this issue. I am using R2BayesX. It seems that the model can maximally contain 20 interactions. When the number of interaction terms exceed 20, the code stops working. Here is a piece of toy code. rm(list=ls()) library(BayesX) library(R2BayesX) #data generating model f2<-function(x1,x2,x3,x4) { y<-2*sin(pi*x1)*1.5+exp(2*x2)/3+2 * sin(4 * pi * (x3

Is there a way to apply paste to?list(form1 = EQ1, form2 = EQ2, form3 = EQ3, form4 = EQ4)?such that I don't have to write form1=EQ1 for all my models?(I might have a list of 20 or more)? I also need the EQs to read the formulas associated with them. For example, below, I was able to automate the name assignment but I could not figure out how to?to set up the list using?paste or other

#### I checked through every 3 factor * 3 loading case. #### While, 4 factor * 3 loading failed. #### the data is 6 factor * 3 loading require(sem); cor18<-read.moments(); 1 .68 1 .60 .58 1 .01 .10 .07 1 .12 .04 .06 .29 1 .06 .06 .01 .35 .24 1 .09 .13 .10 .05 .03 .07 1 .04 .08 .16 .10 .12 .06 .25 1 .06 .09 .02 .02 .09 .16 .29 .36 1 .23 .26 .19 .05 .04 .04 .08 .09 .09 1 .11 .13 .12 .03 .05 .03

Dette er en melding med flere deler i MIME-format. --=_alternative 004C4E4A00257091_= Content-Type: text/plain; charset="US-ASCII" Yes. so (x1*x2*x3*x4*x5*x6*x7*x8)^2 = (x1+x2+x3+x4+x5+x6+x7+x8)^8 ? and there is a difference in (x1*x2*x3*x4*x5*x6*x7*x8)^2 and (x1*x2*x3*x4*x5*x6*x7*x8) althoug the resulting formulas are the same, or? This fikses my problem, but R still crashes for the

On Wed, 5 Oct 2005 Hallgeir.Grinde at elkem.no wrote: > And some more informastion I forgot. > R does not crash if I write out the formula: > > set.seed(123) > x1 <- runif(1000) > x2 <- runif(1000) > x3 <- runif(1000) > x4 <- runif(1000) > x5 <- runif(1000) > x6 <- runif(1000) > x7 <- runif(1000) > x8 <- runif(1000) > y <-

On Wed, 5 Oct 2005 Hallgeir.Grinde at elkem.no wrote: > Yes. > so (x1*x2*x3*x4*x5*x6*x7*x8)^2 = (x1+x2+x3+x4+x5+x6+x7+x8)^8 ? Yes in the sense that the simplified formula given by terms() is the same. > and there is a difference in > (x1*x2*x3*x4*x5*x6*x7*x8)^2 > and > (x1*x2*x3*x4*x5*x6*x7*x8) > althoug the resulting formulas are the same, or? The first is reduced to the

Dette er en melding med flere deler i MIME-format. --=_alternative 004613C000257091_= Content-Type: text/plain; charset="US-ASCII" And some more informastion I forgot. R does not crash if I write out the formula: set.seed(123) x1 <- runif(1000) x2 <- runif(1000) x3 <- runif(1000) x4 <- runif(1000) x5 <- runif(1000) x6 <- runif(1000) x7 <- runif(1000) x8 <-

Hi there, I want to estimate simultaneous equation model with panel data. The model looks as follows Y1=a0+a1*X1+a2*X2 Y2=b0+b1*X2+b2*X1 X1=Z1-(Y1/a1) X2=Z2-(Y2/b1) I In this model Y1, Y2, X1 and X2 are endogenous variables; Z1, Z2 are exogenous variables and a0, a1, a2, b0, b1 and b2 are parameters. Could any one please help me how to estimate this model in R. Thanking you in anticipation

> From: Peter Dalgaard > > Hallgeir.Grinde at elkem.no writes: > > > Dette er en melding med flere deler i MIME-format. > > --=_alternative 004613C000257091_= > > Content-Type: text/plain; charset="US-ASCII" > > > > And some more informastion I forgot. > > R does not crash if I write out the formula: > > > > set.seed(123)

Dear Helplist, I want to produce forecasts from a structural equation model. With the SEM package the model setup and its estimation is possible. However, I have not figured out how to obtain ex ante forecasts, i.e. applying the Gauss-Seidel algorithm to the estimated structural equations for provided values of the exogenous variables (i.e.: y_t = -inv(A)*B*x_t). Does anyone know if the there is

I am looking for study materisl?on how to conduct 'small area estimation' using structural equations models in R for both longtudinal and repeated cross-section data.?Tried google did not work. There are other regression technique my interest is on structural equation models.?

Hi All, I'd like to build a package for the community that replicates the output produced by SAS "proc varclus". According to the SAS documentation, the first few steps are: 1. Find the first two principal components. 2. Perform an orthoblique rotation (quartimax rotation) on eigenvectors. 3. Assign each variable to the rotated component with which it has the higher squared

Hi all, I am using package lavaan and have created a structural equation model with two exogenous and seven endogenous variables with the following relationships #specify the model m1 = ' # regressions D ~ ma + hs + b4 + b5 + b15 + b16 ma ~ hs + b4 + b5 + b15 + b16 hs ~ b4 + b5 + b15 + b16 b4 ~ el + la b5 ~ el + la

Dear R users, Apologies for the total beginner's question. I was wondering whether you could tell me if there is a structural equation modelling function that can handle binary data i.e. in similar manner to the GLM function with a binomial family. Best wishes, Mario

Dear r-help list members, I'm teaching a one-day workshop on "An Introduction to Structural Equation Modeling with the sem Package for R" at McMaster University in Hamilton, Ontario, Canada, on November 22. The workshop is open to non-McMaster attendees at a small charge. Further information, including on how to register, is in the attached poster. Best, John