[R] MCMC Estimation for Four Parametric Logistic (4PL) Item Response Model

[ProfJCNash]

If you have the expression of the model, package nlsr should be able to
form the Jacobian analytically for nonlinear least squares. Likelihood
approaches allow for more sophisticated loss functions, but the
optimization is generally much less reliable because one is working
with essentially squared quantities and possibly multiple minima where
some are not the ones you want.

JN

On 2018-01-18 12:32 PM, Doran, Harold wrote:
> I know of no existing functions for estimating the parameters of this model using MCMC or MML. Many years ago, I wrote code to estimate this model using marginal maximum likelihood. I wrote this based on the using nlminb and gauss-hermite quadrature points from statmod. 
> 
> I could not find that code to share with you, but I do have code for estimating the 3PL in this way and you could modify the likelihood for the upper asymptote yourself.
> 
> 
> 
> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of ALYSSA FATMAH MASTURA
> Sent: Thursday, January 18, 2018 10:15 AM
> To: r-help at r-project.org
> Subject: [R] MCMC Estimation for Four Parametric Logistic (4PL) Item Response Model
> 
> Good day Sir/Ma'am! This is Alyssa Fatmah S. Mastura taking up Master of Science in Statistics at Mindanao State University-Iligan Institute Technology (MSU-IIT), Philippines. I am currently working on my master's thesis titled "Comparing the Three Estimation Methods for the Four Parametric Logistic (4PL) Item Response Model". While I am looking for a package about Markov chain Monte Carlo (MCMC) method for 4PL model in this R forum, I found an sirt package of an MCMC method but only for the three parametric normal ogive (3PNO) item response model. However, my study focus on 4PL model. In line with this, I would like to know if there exist a function of MCMC method for 4PL model in R language. I am asking for your help to inform me if such function exist. I highly appreciate your response on this matter. Thank you so much. Have a great day ahead!
> 
> 
> 
> Alyssa
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