[Rasch] local independence

SR Millis srmillis at yahoo.com
Fri Sep 6 04:42:17 EST 2013


Callie,

As I understand it, the PROMIS folks are coming from a different perspective: the 2-PL IRT model---and not the Rasch model.  However, I don't know if that guides their approach to residual analysis.

Scott
~~~~~~~~~~~
Scott R Millis, PhD, ABPP, CStat, PStat®
Board Certified in Clinical Neuropsychology, Clinical Psychology, & Rehabilitation Psychology 
Professor
Wayne State University School of Medicine
Email:  aa3379 at wayne.edu
Email:  srmillis at yahoo.com
Tel: 313-993-8085

--------------------------------------------
On Thu, 9/5/13, Tyner, Callie <callietyner at PHHP.UFL.EDU> wrote:

 Subject: Re: [Rasch] local independence
 To: "rasch at acer.edu.au" <rasch at acer.edu.au>
 Date: Thursday, September 5, 2013, 12:20 PM
 
 
 
  
 #yiv679122266 P
 {margin-top:0;margin-bottom:0;}
 
 
 Thanks Mike for the input
 
 
 
 I got the idea to examine EFA residuals from the PROMIS
 (Reeve, et al., 2007) paper on item calibration 
 [Reeve, B. B., Hays, R. D., Bjorner, J. B., Cook, K. F.,
 Crane, P. K., Teresi, J. A., … Cella, D. (2007).
 Psychometric evaluation and calibration of health-related
  quality of life item banks: Plans for the Patient-Reported
 Outcomes Measurement Information System (PROMIS). Medical
 Care, 45(5), S22-S31.
 doi:10.1097/01.mlr.0000250483.85507.04]
 
 
 
 Here the authors give the following methods for assessing
 items:
 
 II. Evaluate Assumptions of the Item Response
 Theory (IRT) Model
 
 A. Unidimensionality
 
      1. Confirmatory Factor Analysis
 (CFA) using polychoric correlations (one-factor and
 bi-factor models)
 
      2. Exploratory Factor Analysis will
 be performed if CFA shows poor fit
 
 B. Local independence
 
      1. Examine residual correlation
 matrix after first factor removed in factor analysis
 
      2. IRT-based tests of local
 dependence
 
 C. Monotonicity
 
 1. Graph item mean scores conditional on total score minus
 item score
 
 2. Examine initial probability functions from nonparametric
 IRT models
 
 
 
 
 I've underlined the part that references looking at the
 residual correlation matrix from the factor analysis. 
 Are other people not using this method?
 
 
 
 Thanks all for the edification and discussion,
 
 -Callie
 
 
 
 
 
 ________________________________________
 
 From: rasch-bounces at acer.edu.au [rasch-bounces at acer.edu.au]
 on behalf of Mike Linacre [mike at winsteps.com]
 
 Sent: Thursday, September 05, 2013 10:55 AM
 
 To: rasch at acer.edu.au
 
 Subject: Re: [Rasch] local independence
 
 
 
 Thank you for the questions, Callie.
 
 
 
 EFA residuals are not the same as Rasch residuals. EFA
 residuals are
 
 "observed correlations - expected correlations"
 
 
 
 Rasch residuals are "observed data values - expected
 data values". They
 
 are correlated by pairs of items (variables) across persons
 (cases) in
 
 Winsteps Table 23.99.
 
 
 
 If there are large EFA residuals, then some possibilities
 are (1) more
 
 factors need to be extracted, or (2) the data need to be
 transformed, or
 
 (3) the data need to be pruned.
 
 
 
 I cannot see a direct connection between EFA residuals and
 local
 
 independence, perhaps someone else can ....
 
 
 
 Mike L.
 
 
 
 On 9/5/2013 7:24 AM, Tyner, Callie wrote:
 
 > Thanks Scott,
 
 > I am looking at this here:
 
 >
 http://www.winsteps.com/winman/index.htm?table23_99.htm
 
 >
 
 > Do you know what "TAP" means in the example
 table? I'm trying to
 
 > understand how to interpret this table.
 
 >
 
 > I've been running my EFA and residual correlations
 in R, where the
 
 > output is more of a traditional correlation matrix.
 
 >
 
 > Thanks for your help!
 
 > -Callie
 
 
 
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