JSM 2011 Online Program

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

Abstract Details

Activity Number: 42
Type: Contributed
Date/Time: Sunday, July 31, 2011 : 2:00 PM to 3:50 PM
Sponsor: Section for Statistical Programmers and Analysts
Abstract - #302027
Title: Linear Logistic Test Model: Using SASĀ® to Simulate the Decomposition of Item Difficulty by Algorithm, Sample Size, Cognitive Component, and Time-to-Convergence
Author(s): George T. MacDonald*+ and Jeffrey Kromrey
Companies: University of South Florida and University of South Florida
Address: David C. Anchin Center, Tampa, FL, 33620,
Keywords: LINEAR LOGISTIC TEST MODEL ; PROC NLMIXED ; LLTM
Abstract:

Fischer (1973) introduced a model called The Linear Logistic Test Model (LLTM) that is capable of bridging cognitive processing models and psychometric models. In his mathematics study, he found that differentiating calculus items could be explained by eight basic cognitive operations. He postulated that item difficulty could be re-parameterized to express these operations. LLTM can be coded in SAS using PROC NLMIXED. Clustering items within persons is considered by many to be a multi-level approach. Because no algorithm method exists that always finds the global optimum, and given the array of optimization algorithms available, coders may well want to know which algorithms work best under various test conditions. To provide some answers to these questions, a simulation study was undertaken to determine the utility of the algorithm methods available in PROC NLMIXED according to varying s


The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2011 program




2011 JSM Online Program Home

For information, contact jsm@amstat.org or phone (888) 231-3473.

If you have questions about the Continuing Education program, please contact the Education Department.