Displaying 20 results from an estimated 7000 matches similar to: "sem package, suppress warnings"
2011 Dec 01
3
FIML with missing data in sem package
Is there a way to use full information maximum likelihood (FIML) to
estimate missing data in the sem package? For example, suppose I have a
dataset with complete information on X1-X3, but missing data (MAR) on X4.
Is there a way to use FIML in this case? I know lavaan and openmx allow you
to do it, but I couldn't find anything in the documentation for the sem
package. Thanks!
--
Dustin Fife
2011 Nov 09
1
path.diagram in SEM--display covariances without variances
Forgive me if I'm posting to the wrong place....It's my first time posting.
Here's the situation: I'm using the sem package and making path
diagrams using path.diagrams. Suppose I have the following code:
#install.packages("ggm")
require(ggm)
cor = rcorr(7)
nm = c("SOF", "IWF", "PWF", "FSC", "FSF", "EF",
2012 Jul 09
2
mfrow and centering plots when there's an odd number
Let me start with an example:
par(mfrow=c(2,3))
for (i in 1:5){
x = rnorm(100)
y = .5*x + rnorm(100, 0, sqrt(1-.5^2))
plot(x,y)
}
Note that there's five plots and six spaces for those plots via mfrow,
leaving one row empty. Is there a way to have the bottom two plots
centered? I think it looks weird to have them left-justified. Thanks in
advance for the help!
--
Dustin Fife
PhD
2012 May 29
2
setting parameters equal in lm
Forgive me if this is a trivial question, but I couldn't find it an answer
in former forums. I'm trying to reproduce some SAS results where they set
two parameters equal. For example:
y = b1X1 + b2X2 + b1X3
Notice that the variables X1 and X3 both have the same slope and the
intercept has been removed. How do I get an estimate of this regression
model? I know how to remove the intercept
2013 Jan 29
1
identify non-recursive models
Hi,
I'm working on a project that will generate RAM matrices at random. What I
want to do is to be able to automatically identify if the model is
non-recursive. For example, the following RAM matrix has a non-recursive
loop (going from A to B to C to A):
n.recursive <- data.frame(matrix(c("A", "B", 1,
"B", "C", 1,
2007 Jun 27
1
SEM model fit
I wonder if someone could explain why, when I perform confirmatory
factor-analysis model using polychoric correlations why I do not get an
estimated confidence interval for the RMSEA. My experience with these type
models is that I would obtain a confidence interval estimate. I did not get
any warning messages with the output.
RESULTS:
Model Chisquare = 1374 Df = 185 Pr(>Chisq) = 0
2005 Jun 23
1
Stop Warnings for Invalid Factor Level, NAs generated?
How can I stop the following warning from occuring?
invalid factor level, NAs generated in: "[<-.factor"(`*tmp*`, iseq, value =
structure(1, .Label = "12", class = "factor"))
The Label messages are for "5", "8", "12" and "46". I want the NAs to be
generated as needed.
Is this causing R to slow down by generating the warning
2010 Aug 11
1
sem & psych
Dear R users,
I am trying to simulate some multitrait-multimethod models using the
packages sem and psych but whatever I do to deal with models which do not
converge I always get stuck and get error messages such as these:
"Error in summary.sem(M1) : coefficient covariances cannot be computed"
"Error in solve.default(res$hessian) : System ist f?r den Rechner singul?r:
reziproke
2009 Aug 07
1
Bug in nlm, found using sem; failure in several flavors (PR#13881)
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Hello,
There appears to be a bug in the nlm function, which I
2013 Feb 09
1
Troubleshooting underidentification issues in structural equation modelling (SEM)
Hi all, hope someone can help me out with this.
Background Introduction
I have a data set consisting of data collected from a questionnaire that I
wish to validate. I have chosen to use confirmatory factor analysis to
analyse this data set.
Instrument
The instrument consists of 11 subscales. There is a total of 68 items in
the 11 subscales. Each item is scored on an integer scale between 1 to 4.
2012 Jun 05
0
propensity score matching estimates?
I'm using the "Match" package to do propensity score matching. Here's some
example code that shows the problem that I'm having (much of this code is
taken from the Match package documentation):
*data(lalonde)
glm1 <- glm(treat~age + I(age^2) + educ + I(educ^2) + black +
hisp + married + nodegr + re74 + I(re74^2) + re75 + I(re75^2)
+
u74 + u75,
2009 Aug 07
1
Bug in nlm, found using sem; failure in several flavors (PR#13883)
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Hi Jeff,
=09As mentioned in my message, I *did* replicate on another platform.=20
One platform was
2005 Jun 02
1
nls.control: increasing number of iterations
Hello,
I'm using the nls function and would like to increase the number of
iterations. According to the documentation as well as other postings on
R-help, I've tried to do this using the "control" argument:
nls(y ~ SSfpl(x, A, B, xmid, scal), data=my.data,
control=nls.control(maxiter=200))
but no matter how much I increase "maxiter", I get the following error
2002 Jul 18
1
sem: incorrect parameter estimates
Hello.
I am getting results from sem that are not correct (that's assuming
that the results from my AMOS 4.0 software are correct). sem does not
vary some of the parameters substantially from their starting values,
and the final estimates of those parameters as well as the model
chisquare value are incorrect. I've attached some code that
replicates the problem. The parameters in
2011 Feb 08
1
SEM: question regarding how standard errors are calculated
Sorry if this question has been asked previously, I searched but found
little. There also doesn't seem to be a dedicated SEM list-serv so hopefully
this will find its way to the appropriate audience.
In discussing SEM with a colleague I mentioned that a model they were
fitting in AMOS was equivalent to a linear regression and that the
coefficients would be the same. This of course was the
2009 Apr 24
1
Sem and nlm and ols instead of ml
Dear colleagues,
Has anybody any experience using the sem package to fit structural
equation models using a fitting function other than ML? I have heard tell
that OLS may provide better estimates when using standardized matrices
generated from small sample sizes, so I was interested in comparing the two
for a few models. However, ML appears to be hard-coded into the source for
sem...but maybe
2007 Jan 24
1
solving a structural equation model using sem or other package
I am trying to work my way through the book "Singer, JD and Willett, JB, Applied Longitudinal Data Analysis. Oxford University Press, 2003" using R. I have the SAS code and S-Plus code from the UCLA site (doesn't include chapter 8 or later problems). In chapter 8, there is a structural equation/path model which can be specified for the sem package as follows
S <- cov(al2)
2009 Dec 26
5
Is SEM package of R suitable for sem analysis
Dears,
I'm a college student and In doing my statistics homework.
I use R with SEM package as my tool for sem analysis,
but my teacher told me AMOS is more suitable for such analysis.
Could someone help tell me whether it is true
that some commercial software is better accepted in academic fields?
Sorry if I should not post such topics here.
--
Best Regards,
Reeyarn T. Lee
Accounting
2006 Feb 07
1
elements from 'sem' function
Hi,
I would like to print elements from sem (structural equation modeling)
function (e.g., model-reproduced covariance matrix (C); estimated asymptotic
covariance matrix of parameter estimates (cov)).
How can I do this?
Thanks,
Andr??
--
Andr?? Tavares Corr??a Dias
Laborat??rio de Ecologia Vegetal
Universidade Federal do Rio de Janeiro
CCS-IB-Departamento de Ecologia
Caixa Postal 68020
2009 Jul 20
3
Another SEM question
Hello,
I use the function sem the following way
sem.mod <- sem(model, mod.cov, N=109) where the variables are modelled:
Z -> M
Z -> I
Z -> R
M <-> M
I <-> I
R <-> R
Z <-> Z
The output is
...
Normalized Residuals
Min. 1st Qu. Median Mean 3rd Qu. Max.
-7.3300 -0.2750 -0.2670 -0.1290 -0.0369 9.0300
Parameter Estimates
Estimate Std Error z value Pr(>|z|)