2
I am applying the TRI (Item Response Theory) with the package mirt
, in Rstudio. However, when applying the mirt
, processing stops when it reaches 500 iterations. Is it possible to increase the number of iterations? If so, how?
2
I am applying the TRI (Item Response Theory) with the package mirt
, in Rstudio. However, when applying the mirt
, processing stops when it reaches 500 iterations. Is it possible to increase the number of iterations? If so, how?
3
The maximum number of iterations is documented in the package help page, function mirt
.
Of help("mirt")
.
Technical
a list containing lower level technical parameters for estimation. May be: NCYCLES maximum number of EM or MH-RM cycles; defaults are 500 and 2000
Translation Google Translate.
Technical
uma lista contendo parâmetros técnicos de nível inferior para estimação. Talvez: NCYCLES número máximo de ciclos EM ou MH-RM; os padrões são 500 e 2000
Testing with one of the examples that does not converge with the number of standard iterations, the example with the dataset SAT12
, you can see it works.
library(mirt)
data(SAT12)
data <- key2binary(SAT12,
key = c(1,4,5,2,3,1,2,1,3,1,2,4,2,1,5,3,4,4,1,4,3,3,4,1,3,5,1,3,1,5,4,5))
mod2 <- mirt(data, 2, optimizer = 'NR')
#Iteration: 500, Log-Lik: -9441.963, Max-Change: 0.00012
#EM cycles terminated after 500 iterations.
mod2.b <- mirt(data, 2, optimizer = 'NR',
technical = list(NCYCLES = 5000))
#Iteration: 1065, Log-Lik: -9441.950, Max-Change: 0.00010
In this second case went up to the iteration 1065
and has reached tolerance 0.0001
.
1
Bringing the translation of the answer I found in a Google Groups:
"It is on the technical entry list, called NCYCLES:
mod <- mirt(Science, 1, technical = list(NCYCLES = 2000))
source:Google Groups
Thank you very much!!
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Thank you very much!!
– Fabiana Zaffalon