PerFit.PFS {PerFit} | R Documentation |
Compute several person-fit statistics
Description
Compute several person-fit statistics.
Usage
PerFit.PFS(matrix, method=NULL, simplified=TRUE,
NA.method = "Pairwise", Save.MatImp = FALSE,
IP = NULL, IRT.PModel = NULL, Ability = NULL, Ability.PModel = NULL,
mu = 0, sigma = 1)
Arguments
matrix |
Data matrix of dichotomous item scores: Persons as rows, items as columns, item scores are either 0 or 1, missing values allowed. |
method |
Vector of person-fit statistics to be computed. |
simplified |
Logical. If FALSE, a list of |
NA.method |
Method to deal with missing values. The default is pairwise elimination ( |
Save.MatImp |
Logical. Save (imputted) data matrix to file? Default is FALSE. |
IP |
Matrix with previously estimated item parameters: One row per item, and three columns ([,1] item discrimination; [,2] item difficulty; [,3] lower-asymptote, also referred to as pseudo-guessing parameter). In case no item parameters are available then |
IRT.PModel |
Specify the IRT model to use in order to estimate the item parameters (only if |
Ability |
Vector with previoulsy estimated latent ability parameters, one per respondent, following the order of the row index of In case no ability parameters are available then |
Ability.PModel |
Specify the method to use in order to estimate the latent ability parameters (only if |
mu |
Mean of the apriori distribution. Only used when |
sigma |
Standard deviation of the apriori distribution. Only used when |
Details
Function PerFit.PFS
is a wrapper allowing to compute more than one person-fit statistic simultaneously.
Value
If simplified=TRUE
, a N-by-m data frame is returned, where N is the number of respondents and m is the number of methods.
If simplified=FALSE
a list of m PerFit
objects is returned.
Author(s)
Jorge N. Tendeiro tendeiro@hiroshima-u.ac.jp
Examples
# Load the inadequacy scale data (dichotomous item scores):
data(InadequacyData)
# Compute the lzstar, U3, and Ht scores:
PerFit.PFS(InadequacyData, method=c("lzstar", "U3", "Ht"))