Illustrating the use of Item Response Tree GLMMs for the study of behaviour data.

1. Item
response
TreesAndrés López-Sepulcre

2. the Culprits
Janne
Valkonen
Johanna
Mappes
Kate
UMBERS
Sebastiano
DE bonA

3. Measuring
behaviour

4. ITEM
response
Theory

5. How do birds react to
butterfly eyespots?

6. Sebastiano de Bona
TODAY
2:45
Room 8
Escape & Avoidance

7. curious
DATA ignore
startle
flee
attack
curious

8. X
11 5 2 10 10
16 12 11 9 2
TABLES

9. X
11 5 2 10 10
16 12 11 9 2
TABLES
χ2
df=4 = 14.05
p = 0.007

10. X
11 5 2 10 10
16 12 11 9 2
TABLES
Where is the
difference?
χ2
df=4 = 14.05
p = 0.007

11. X
11 5 2 10 10
16 12 11 9 2
TABLES
Where is the
difference?
Realistic
designs?
χ2
df=4 = 14.05
p = 0.007

12. ignore
startle
flee
attack
curious
LINEAR
Mixed
MODELS

13. Fixed effects
ignore
startle
flee
attack
curious
LINEAR
Mixed
MODELS

14. Fixed effects Random effects
ignore
startle
flee
attack
curious
LINEAR
Mixed
MODELS

15. Fixed effects Random effects
Response
ignore
startle
flee
attack
curious
LINEAR
Mixed
MODELS

16. Fixed effects Random effects
Response
ignore
startle
flee
attack
curious
LINEAR
Mixed
MODELS

17. Fixed effects Random effects
Response
ignore
startle
flee
attack
curious
LINEAR
Mixed
MODELS

18. Fixed effects Random effects
Response
ignore
startle
flee
attack
curious
LINEAR
Mixed
MODELS

19. Fixed effects Random effects
Response
ignore
startle
flee
attack
curious
LINEAR
Mixed
MODELS

20. Fixed effects Random effects
Response
ignore
startle
flee
attack
curious
LINEAR
Mixed
MODELS

21. TREEs
ignore
startle
flee
attack
curious

22. TREEs
ignore
startle
flee
attack
curious

23. TREEs
NODES
ignore
startle
flee
attack
curious

24. TREEs
0
1
1
0 0
1
0
1
ignore
startle
flee
attack
curious

25. TREEs
0
1
1
0 0
1
0
1
attack
IND. NODE RESPONSE
B1 n1 1
B1 n2 0
B1 n3 NA
B1 n4 1
attack

26. TREEs
0
1
0
1 0
1
1
0
attack
IND. NODE RESPONSE
B2 n1 1
B2 n2 1
B2 n3 1
B2 n4 NA
flee

27. ignore
startle
flee
attack
curious
Treatment
x Node
Individual
x Node
Response
LINEAR
Mixed
MODELS

28. Fixed Estim. SE P
value
n1 control 3.60 2.28
effect -0.32 1.99 0.87
n2 control -2.57 1.36
effect 3.39 1.61 0.04
n3 control -0.84 0.92
effect -2.80 1.73 0.11
n4 control 1.03 2.28
effect 0.72 2.04 0.72
Random
Individual n1 n2 n3
n1 33.33
n2 6.51 0.51
n3 3.21 0.53 -0.46
n4 12.13 -0.22 -0.95 0.71
IRTree
GLMM

29. Fixed Estim. SE P
value
n1 control 3.60 2.28
effect -0.32 1.99 0.87
n2 control -2.57 1.36
effect 3.39 1.61 0.04
n3 control -0.84 0.92
effect -2.80 1.73 0.11
n4 control 1.03 2.28
effect 0.72 2.04 0.72
Random
Individual n1 n2 n3
n1 33.33
n2 6.51 0.51
n3 3.21 0.53 -0.46
n4 12.13 -0.22 -0.95 0.71
IRTree
GLMM

30. Fixed Estim. SE P
value
n1 control 3.60 2.28
effect -0.32 1.99 0.87
n2 control -2.57 1.36
effect 3.39 1.61 0.04
n3 control -0.84 0.92
effect -2.80 1.73 0.11
n4 control 1.03 2.28
effect 0.72 2.04 0.72
Random
Individual n1 n2 n3
n1 33.33
n2 6.51 0.51
n3 3.21 0.53 -0.46
n4 12.13 -0.22 -0.95 0.71
IRTree
GLMM

31. Fixed Estim. SE P
value
n1 control 3.60 2.28
effect -0.32 1.99 0.87
n2 control -2.57 1.36
effect 3.39 1.61 0.04
n3 control -0.84 0.92
effect -2.80 1.73 0.11
n4 control 1.03 2.28
effect 0.72 2.04 0.72
Random
Individual n1 n2 n3
n1 33.33
n2 6.51 0.51
n3 3.21 0.53 -0.46
n4 12.13 -0.22 -0.95 0.71
IRTree
GLMM

32. escalate?
escalate?
escalate?
escalate?
ESCALATION

33. Flexibility

34. Flexibility
INTERPRETABILITY

35. Flexibility
DATA HUNGRY
INTERPRETABILITY

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37. ThankYOU!

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