person.parameter {eRm} | R Documentation |
Maximum likelihood estimation of the person parameters with spline interpolation for non-observed and 0/full responses.
## S3 method for class 'eRm': person.parameter(object) ## S3 method for class 'ppar': summary(object, ...) ## S3 method for class 'ppar': print(x, ...) ## S3 method for class 'ppar': plot(x, xlab = "Person Raw Scores", ylab = "Person Parameters (Theta)", main = NULL, ...)
object |
Object of class eRm . |
x |
Object of class ppar . |
xlab |
Label of the x-axis. |
ylab |
Label of the y-axis. |
main |
Title of the plot. |
... |
Further arguments to be passed to or from other methods. They are ignored in this function. |
If the data set contains missing values, person parameters are estimated for each missing value subgroup.
The function person.parameter
returns an object of class ppar
containing:
loglik |
Log-likelihood. |
npar |
Number of parameters. |
niter |
Number of iterations. |
thetapar |
Person parameter estimates. |
se.theta |
Standard errors of the person parameters. |
Patrick Mair, Reinhold Hatzinger
Fischer, G. H., and Molenaar, I. (1995). Rasch Models - Foundations, Recent Developements, and Applications. Springer.
Mair, P., and Hatzinger, R. (2007). Extended Rasch modeling: The eRm package for the application of IRT models in R. Journal of Statistical Software, 20(9), 1-20.
Mair, P., and Hatzinger, R. (2007). CML based estimation of extended Rasch models with the eRm package in R. Psychology Science, 49, 26-43.
#Person parameter estimation of a rating scale model data(rsmdat) res <- RSM(rsmdat) pres <- person.parameter(res) print(pres) summary(pres) plot(pres) #Person parameter estimation for a Rasch model with missing values data(raschdat1) raschNA <- raschdat1 raschNA[1:40,1] <- NA #first item not presented raschNA[41:100,2] <- NA #second item not presented res <- RM(raschNA, se = FALSE) #Rasch model without standard errors pres <- person.parameter(res) print(pres) #person parameteres round to 5 digits summary(pres)