On Tue, May 14, 2019 at 3:15 AM car...@web.de wrote:
From my point of view, this has nothing to do with lavaan.
This is correct. It’s an option in R, max.print.
library(lavaan)
model <- '
# latent variable definitions
ind60 =~ x1 + x2 + x3
dem60 =~ y1 + a*y2 + b*y3 + c*y4
dem65 =~ y5 + a*y6 + b*y7 + c*y8
# regressions
QA.GMF =~ ind60:dem60
dem65 ~ QA.GMF
'
fit <- sem(model, data=PoliticalDemocracy)
# play around with printing settings, note this doesn't
# have to do with lavaan
options()$max.print
options(max.print = 100)
modindices(fit)
options(max.print = 500)
modindices(fit)
options(max.print = 1000)
modindices(fit)
With options you can influence the output behavior of R. Regardless, I don't think you really need all modification indices results. Probably it's enough to look at the really relevant results like this:
mi <- modindices(fit)
mi[mi$mi > 10,]
10 is arbitrary, of course.
--
You received this message because you are subscribed to the Google Groups "lavaan" group.
To unsubscribe from this group and stop receiving emails from it, send an email to lavaan+un...@googlegroups.com.
To post to this group, send email to lav...@googlegroups.com.
Visit this group at https://groups.google.com/group/lavaan.
To view this discussion on the web visit https://groups.google.com/d/msgid/lavaan/trinity-071d314d-0d8b-483a-81a4-efca15a3002f-1557821719808%40msvc-mesg-web002.
For more options, visit https://groups.google.com/d/optout.
Responded too quickly. This one is reproducible.
Note, that max.print
is the pieces of information not the number of rows, but as your noted, sort
is the argument to add.
library(lavaan)
model <- '
# latent variable definitions
ind60 =~ x1 + x2 + x3
dem60 =~ y1 + a*y2 + b*y3 + c*y4
dem65 =~ y5 + a*y6 + b*y7 + c*y8
# regressions
dem60 ~ ind60
dem65 ~ ind60 + dem60
'
fit <- sem(model, data=PoliticalDemocracy)
# play around with printing settings, note this doesn't
# have to do with lavaan
options()$max.print
options(max.print = 100)
modindices(fit)
options(max.print = 500)
modindices(fit)
options(max.print = 1000)
modindices(fit)