1. Quentin Frederik Gronau1
Generalization of Recognition Memory Models across YES/NO and Two-Alternative Forced-Choice Tasks Using Ternary Response Options
Quentin Frederik Gronau1
Henrik Singmann2
David Kellen3
Karl Christoph Klauer4
1 University of Amsterdam; 2 University of Zurich; 3 University of Basel; 4 Albert-Ludwigs-Universität Freiburg

2. YES/NO Recognition Memory Task

3. HOUSE BOAT FOOD SEAL RAIN RAIN CAT KING FOOD SEAL HEAVEN
Learning Phase:
HOUSE
BOAT
FOOD
SEAL
RAIN …
Test phase:
old? new?
RAIN
old? new?
CAT
old? new?
KING
old? new?
FOOD
old? new?
SEAL
old? new?
HEAVEN …

4. HOUSE BOAT FOOD SEAL RAIN RAIN CAT KING FOOD SEAL HEAVEN
Learning Phase:
HOUSE
BOAT
FOOD
SEAL
RAIN …
Old Word
New Word
old? new?
RAIN
old? new?
CAT
old? new?
KING
old? new?
FOOD
old? new?
SEAL
old? new?
HEAVEN
Hit
Miss
Correct Rejection
False Alarm …

5. Measurement Models Two-High Threshold (discrete state) Model
(2HTM; Snodgrass & Corwin, 1988)
Unequal-Variance Signal Detection (continuous) Model
(UVSD; Green & Swets, 1966)

6. How can we adequately measure recognition memory?

7. Validating a Ternary Response Scale
HOUSE
old
unsure
new
Such a ternary response scale has already been used (but not validated) by:
Singmann, Kellen, & Klauer (2013, CogSci Proceedings)
Kellen, Singmann, Klauer, & Flade (in revision)
Kellen, Singmann, & Klauer (2014)
Klauer, Dittrich, Scholtes, & Voss (2015)

8. YES/NO Task Two-High Threshold (discrete state) Model
Unequal-Variance Signal Detection (continuous) Model
4 parameters (D0, Dn, gunsure, gold), 4 available df
→ fully identified
4 parameters (μo, σo, c1, c2), 4 available df
→ fully identified

9. Validating a Ternary Response Scale
HOUSE BOAT
left
unsure
right
HOUSE
old
unsure
new
Is this ternary response scale valid?
The experiment: Generalization approach
Test ability to be generalized across two most common recognition memory tasks: YES/NO and Two-Alternative Forced-Choice (2AFC) task
When presenting participants with YES/NO and 2AFC trials for a set of studied words, memory parameters should be the same for both tasks
Jang, Wixted, & Huber (2009) provided evidence that the UVSD can adequately be generalized across these tasks using a 6-point-confidence rating scale
To our knowledge, now such generalization study exists for 2HTM

10. (within participants)
2 tasks
(within participants)
Learning Phase:
HOUSE
Old/New Task
per Block:
50 strong (4 × learned)
50 weak (1 ×)
50 new (0 ×)
HOUSE
old
unsure
new
BOAT
Experiment:
29 participants
550 trials:
2 blocks with 275 words
150 Old/New & 125 2AFC
memory strength manipulation
0.75 s study time ISI
2AFC Task
per Block:
50 strong (4 × learned)
50 weak (1 ×)
25 new/new (0 ×)
old words:
50% old word left
50% old word right
WHITE RAVEN
left
unsure
old
FOOD
SEAL
RAIN
Test phase: …
old? unsure? new?
RAIN
old? unsure? new?
CAT
left? unsure? right?
KING FOOD
left? unsure? right?
COFFEE BED
old? unsure? new?
SEAL
old? unsure? new?
HEAVEN
left? unsure? right?
HOUSE SPOON …

11. Two-Alternative Forced-Choice (2AFC) Task
Two-High Threshold (discrete state) Model
Unequal-Variance Signal Detection (continuous) Model

12. Unrestricted Models 2HTM separate parameters: G²(174)= 187.21, p=.23
6.9% individual misfits
UVSD separate parameters:
G²(174)= , p=.25
10.34% individual misfits

13. Correlation Memory Parameters Different Tasks

14. Memory Parameters Restricted Across Tasks
2HTM:
Do and Dn restricted to be equal across tasks
G²(261)= , p= .0008
17.24% individual misfits
ΔG²(87)= , p < .001
Critical χ² in compromise power analysis (Faul, Erdfelder, Lang, & Buchner (2007):
24.14% individual misfits
UVSD:
μo and σo restricted to be equal across tasks
G²(261)= , p = .004
17.24% individual misfits
ΔG²(87)= , p < .001
Critical χ² in compromise power analysis (Faul, Erdfelder, Lang, & Buchner (2007):
24.14% individual misfits

15. Conclusion
Both the Two-High Threshold Model (2HTM) and the Unequal-Variance Signal Detection Model (UVSD) are able to adequately account for participants‘ performance across YES/NO and 2AFC task
Ternary response scale is a parsimonious and valid way to measure recognition memory that should be integrated in researchers‘ toolbox which yields full model identifiablity for the simplest recognition memory tasks

16. Thanks to my Collaborators