[R] error in model specification for cfa with lavaan-package

[yrosseel]

Dear Alain,

As for the first error ("sample covariance can not be inverted"): Mike 
is right: with only 10 observations and 16 variables, the ML estimation 
of the sample cov produces a covariance matrix that is not positive 
definite, and hence the inversion (deliberately) fails.

The lesson for me is that lavaan should simply check for this situation 
(p > N), and refuse to proceed (with a gentle and more informative error 
message).

As for the second error ("Error in start.idx[i]:end.idx[i] : NA/NaN 
Argument"): the first argument of cfa() must be a model syntax, not a 
lavaanified object.

The 'lavaanify' function is useful to learn about lavaan, and to export 
the model specification to other software packages, but you should not 
pass a 'lavaanified' object to the cfa/sem/growth functions directly 
(although this may work in the future).

Moreover, to get a 'complete' parameter list, you need to specify a 
number of additional arguments:

model <- model <- lavaanify(cfa.model, auto.fix.first = TRUE, auto.var = 
TRUE, auto.cov.lv.x = TRUE)

(see the 'Details' section in the man page of cfa() for a complete list).

Hope this helps,

Yves.


On 06/01/2011 12:31 PM, D. Alain wrote:
> Dear R-List,
>
> (I am not sure whether this list is the right place for my
> question...)
>
> I have a dataframe df.cfa
>
> df.cfa<-data.frame(x1=c(5,4,1,5,5,NA,4,NA,NA,5),x2=c(2,3,3,3,NA,1,2,1,2,1),x3=c(5,3,4,1,5,5,5,5,5,5),x4=c(5,3,4,5,5,5,5,5,5,5),x5=c(5,4,3,3,4,4,4,5,NA,5),x6=c(3,5,2,1,4,NA,NA,5,3,4),x7=c(5,4,3,4,4,3,4,NA,NA,4),x8=c(5,5,3,4,5,4,5,4,5,5),x9=c(5,1,1,1,NA,3,3,2,2,3),x10=c(5,5,2,3,4,3,1,3,2,5),x11=c(5,4,4,5,5,4,5,4,5,5),x12=c(5,4,5,5,5,4,5,5,5,5),x13=c(5,4,4,5,5,5,5,5,5,5),x14=c(5,3,3,NA,5,4,5,3,NA,5),x15=c(4,4,4,3,4,5,2,4,5,5),x16=c(5,4,3,3,4,4,3,3,4,5))
>
>
>
>
>
> and I want to carry out a confirmatory factor analysis using the
> "cfa" function (lavaan).
>
> library(lavaan)
>
> then I specify my model
>
> cfa.model<-'      f1=~x1+x2+x3+x4+x5 f2=~x6+x7+x8+x9+x10+x11
> f3=~x12+x13+x14+x15+x16 '
>
> and run the cfa routine
>
> fit<-cfa(cfa.model,data=df.cfa,missing="ml")
>
> The output is an error message (here partly in german)
>
> "Error in chol.default(S) : der führende Minor der Ordnung 4 ist
> nicht positiv definit Fehler in Sample(data = data, group = group,
> sample.cov = sample.cov, sample.mean = sample.mean,  : sample
> covariance can not be inverted"
>
> Then I tried to "lavaanify" my model specification first
>
> cfa.model<- lavaanify(cfa.model)
>
> id lhs op rhs user group free ustart fixed.x   label eq.id
> free.uncon 1   1  f1 =~  x1    1     1    1     NA       0  f1=~x1 0
> 1 2   2  f1 =~  x2    1     1    2     NA       0  f1=~x2 0
> 2 3   3  f1 =~  x3    1     1    3     NA       0  f1=~x3 0
> 3 4   4  f1 =~  x4    1     1    4     NA       0  f1=~x4 0
> 4 5   5  f1 =~  x5    1     1    5     NA       0  f1=~x5 0
> 5 6   6  f2 =~  x6    1     1    6     NA       0  f2=~x6 0
> 6 7   7  f2 =~  x7    1     1    7     NA       0  f2=~x7 0
> 7 8   8  f2 =~  x8    1     1    8     NA       0  f2=~x8 0
> 8 9   9  f2 =~  x9    1     1    9     NA       0  f2=~x9 0
> 9 10 10  f2 =~ x10    1     1   10     NA       0 f2=~x10 0
> 10 11 11  f2 =~ x11    1     1   11     NA       0 f2=~x11 0
> 11 12 12  f3 =~ x12    1     1   12     NA       0 f3=~x12 0
> 12 13 13  f3 =~ x13    1     1   13     NA       0 f3=~x13 0
> 13 14 14  f3 =~ x14    1     1   14     NA       0 f3=~x14 0
> 14 15 15  f3 =~ x15    1     1   15     NA       0 f3=~x15 0
> 15 16 16  f3 =~ x16    1     1   16     NA       0 f3=~x16 0
> 16
>
> I run cfa again
>
> fit<-cfa(cfa.model,data=df.cfa,missing="ml")
>
> And this time I get another error information
>
> "Error in start.idx[i]:end.idx[i] : NA/NaN Argument"
>
> I must admit that I am stuck, can anyone help?
>
> Thanks, Alain [[alternative HTML version deleted]]
>
>
>
>
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