Exploring Loglikelihood Surface for IRT Models
Unidimensional Item Response Model
Compensatory Two-Dimensional Item Response Model
Partially Compensatory Two-Dimensional Item Response Models
ENTER THE ITEM PARAMETERS:
Item Discrimination (a)
Item Difficulty (b)
Lower Bound (g)
Upper Bound (d)
Choose the X-axis parameter
a
b
g
d
Choose the Y-axis parameter
a
b
g
d
Draw Loglikelihood Surface
Calculations take 10-12 seconds...
For questions and feedback:
Cengiz Zopluoglu
cengiz@uoregon.edu
Personal Website
Quantitative Research Methods Program
College of Education at UO
ENTER THE ITEM PARAMETERS:
Item Discrimination - Dimension 1 (a1)
Item Discrimination - Dimension 2 (a2)
Item Intercept (c)
Lower Bound (g)
Upper Bound (d)
Correlation between dimensions
Choose the X-axis parameter
a1
a2
c
g
d
Choose the Y-axis parameter
a1
a2
c
g
d
Draw Loglikelihood Surface
Calculations take 10-12 seconds...
For questions and feedback:
Cengiz Zopluoglu
cengiz@uoregon.edu
Personal Website
Quantitative Research Methods Program
College of Education at UO
ENTER THE ITEM PARAMETERS:
Item Discrimination - Dimension 1 (a1)
Item Discrimination - Dimension 2 (a2)
Item Difficulty - Dimension 1 (b1)
Item Difficulty - Dimension 2 (b2)
Lower Bound (g)
Upper Bound (d)
Correlation between dimensions
Choose the X-axis parameter
a1
a2
b1
b2
g
d
Choose the Y-axis parameter
a1
a2
b1
b2
g
d
Draw Loglikelihood Surface
Calculations take 10-12 seconds...
For questions and feedback:
Cengiz Zopluoglu
cengiz@uoregon.edu
Personal Website
Quantitative Research Methods Program
College of Education at UO