compute_score
computes the the IPOQ-LL/IPOQ-LL-DIF score of an instrument (included set) of the given initial survey.
While compute_scores
computes the IPOQ-LL/IPOQ-LL-DIF score of many (more than one) instruments (included sets) of
the given initial survey simultanously.
compute_score(
X,
incl_set,
type = c("ipoqll", "ipoqlldif"),
groups_map = c(),
init_par_iq = c(),
init_par_oq = c(),
setting_par_iq = c(),
setting_par_oq = c(),
method = c("fast", "novel")
)compute_scores(
X,
incl_sets,
type = c("ipoqll", "ipoqlldif"),
step_direct = c("fixed", "forward", "backward"),
groups_map = c(),
init_par_iq = c(),
init_par_oq = c(),
setting_par_iq = c(),
setting_par_oq = c(),
cores = NULL,
method = c("fast", "novel"),
timeLimit = 3600
)
# S3 method for score
summary(object, ...)
compute_score
will return a vector which contains in-questionnaire log likelihood (IQ-LL(-DIF)), out-of-questionnaire log likelihood(OQ-LL(-DIF)),
IPOQ-LL(-DIF), included set's items' number in the given initial survey, the estimated theta parameters, the estimated items' parameters in the included set,
and the estimated items' parameters in the excluded set, sequentially.
compute_scores
will return a matrix as a result of the rbind
operation of the compute_score
's result.
A matrix or data.frame of the observed responses (ordinal or binary response).
A vector of the items (columns) number in the data.frame X that are included in the included set.
The type of the score. ipoqll
if we ignore the presence of the DIF and ipoqlldif
if we want to consider the DIF effect.
Matrix to map the respondents to the DIF groups.
Initial values of the parameters in the included set before the estimation begin.
Initial values of the parameters in the excluded set before the estimation begin.
The coordinate descent optimisation setting of the included set. See autoRasch::autoRaschOptions()
cd_control
parameter.
The coordinate descent optimisation setting of the excluded set. See autoRasch::autoRaschOptions()
cd_control
parameter.
The implementation option of log likelihood function. fast
using a c++
implementation and novel
using an R
implementation.
A matrix as a results of a rbind
of incl_set
.
How will you compute the criterion score. fixed
for the given itemset,
forward
computes all the scores of the possible combination of items if an item is added to the given set,
backward
computes all the scores of the possible combination of items if an item is removed to the given set.
Number of cores that is used in the paralellization.
To limit the execution time of scores' computation.
The object from the class score
. The result of the score computation.
further argument passed or from other method.
ipoqll_score <- compute_score(shortDIF,incl_set = c(1:3),type = "ipoqll")
summary(ipoqll_score)
if (FALSE) {
ipoqll_scores <- compute_scores(shortDIF,incl_set = rbind(c(1:3),c(2:4)),
type = "ipoqll", cores = 2)
View(ipoqll_scores)
}
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