itemPar1PL permits to get item parameter estimates from the Rasch or 1PL model. The output is ordered such that it can be directly used
 with the general itemParEst command, as well as the methods of Lord (difLord) and Raju (difRaju) and
 Generalized Lord's (difGenLord) to detect differential item functioning.
The data is a matrix whose rows correspond to the subjects and columns to the items.
Missing values are allowed but must be coded as NA values. They are discarded for item parameter estimation.
 
The estimation engine is set by the engine argument. By default (engine="ltm"), the Rasch model is fitted using marginal maximum likelihood, by means of 
 the function rasch from the ltm package (Rizopoulos, 2006). The other option, engine="lme4", permits to fit the Rasch model as a generalized 
 linear mixed model, by means of the glmer function of the lme4 package (Bates and Maechler, 2009).
With the "ltm" engine, the common discrimination parameter is set equal to 1 by default. It is possible to fix another value through the argumentdiscr.
 Alternatively, this common discrimination parameter can be estimated (though not returned) by fixing discr to NULL. See the functionalities of 
 rasch command for further details.