## Item Response Theory and Other Psychometric Issues

9/18/2017

Hays, Ron D. Spritzer, Karen L. (September 18, 2017 -
updated).
Estimating theta using
existing item parameters with flexMIRT^{®} software.

2/25/2016

Estimating reliability from CAT

12/18/2014

SAS^{® }PROC IRT
Example

(promisgph.pdf results)

Item Response Theory: What It Is and How You
Can Use the IRT Procedure to Apply It
- Xinming An and Yiu-Fai Yung, SAS Institute, Paper SAS364-2014

3/12/2014

Hochberg, Y.
(1988).
A sharper Bonferroni procedure for multiple
tests of significance.
__Biometrika__, __75__, 800-802.

Background on computations:
hochberg.doc

SAS code to compute hochberg adjustment:

example 1: hochberg.sas,
hochberg.lst

example 2: hochberg2.sas,
hochberg.lst

STATA has a module that can implement hochberg
adjustment (install
multproc):

example 1: hochberg.log

example 2: hochberg2.log

8/20/2013

Cohen's rule of thumb for correlations that correspond to effect
size rules of 0.20 SD, 0.50 SD and 0.80 SD are as follows:

0.100 is small correlation

0.243 is medium correlation

0.371 is large correlation

Note, however, that r's of 0.10, 0.30 and 0.50 are often cited as
small, medium and large, respectively.

Effect size calculators:
http://www.polyu.edu.hk/mm/effectsizefaqs/calculator/calculator.html

More about effect sizes:
http://effectsizefaq.com/

__
6/23/2011
__
Linear transformation of item parameters
(using, e.g., Stocking-Lord transformation constants):

Transformed slope = Slope/Slope transformation constant

Transformed thresholds are: (Threshold * Slope transformation constant) + Intercept

Transformed thresholds are: (Threshold * Slope transformation constant) + Intercept

__
10/8/2010
__

Information Reliability SE

10
0.90 0.32

6.7
0.85 0.39

5
0.80 0.45

Note: SE = standard error. Calculations are for z-scores metric and
ML estimation.

Formulas:

Information = 1/(1-reliability) = 1/SE**2

Reliability = (INF-1)/INF = 1 - SE**2

SE = 1/SQRT(INF) = SQRT(1-Reliability)

__
7/27/2009
__Reeve et al. (2007)
in Medical Care provided the following guidelines for good fit to

a one-factor model (for evaluation of unidimensionality assumption):

CFA>0.95

RMSEA < 0.06

SRMR < 0.08

Average absolute residual correlation < 0.10

Summary of steps to produce raw score conversion to theta estimates for PROMIS global mental health items (6/22/2009)

Karen Spritzer with assistance from Ron D. Hays

Summary of steps to produce raw score conversion to theta estimates for PROMIS global physical health items (6/19/2009)

Karen Spritzer with assistance from Ron D. Hays

The authors are eternally grateful to Seung Choi for his expertise and guidance.

__
6/11/2009
__PPV =
(sensitivity)(prevalence)/(sensitivity)(prevalence)+(1-specificity)(1-prevalence))

PPV=postive predictive value

NPV=(specificity)(1-prevalence)/(specificity)(1-prevalence)+(1-sensitivity)(prevalence))

NPV=negative predictive value

Rasch Model infit and outfit mean square statistics

*(4/6/2009)*

The infit statistic provides information about responses within a patient’s ability level. The outfit statistic assesses items that are far beyond a person’s ability level. Poor item fit has been defined as infit or outfit < 0.6 or > 1.4