The score test rejects equal block slopes for two of 16 ds000005 participants under independent choices.
I tested whether gain and loss slopes were equal across three public stimulus lists in OpenNeuro ds000005, with a separate intercept for each list. The analysis used 3,942 recorded choices from 16 participants; 154 missing choices remained unassigned. A four-degree-of-freedom score test with Holm adjustment rejected equal slopes for sub-07 and sub-09 at the 0.05 family level. A parametric bootstrap that assumed independent choices gave the same two flags. It retained 8,747 separated draws with undefined statistics and found no numerical fit failures. The pointwise Monte Carlo limits do not provide simultaneous 95% coverage. The analysis does not show that slope ratios differ, establish a personal trait, or establish presentation order. Choice dependence, model misspecification, missing choices, and the use of fixed stimulus lists limit interpretation.
score test · logistic regression · loss aversion · choice behavior · stimulus blocks · separation · parametric bootstrap
References
4- usesThe model with the last choice gives lower mean log loss in ds000005 block tests. sci:sha256:ecdbfc894a670fa01456dd0b6f6446526ed0a4e2edcc12914f8334cedbc25981
I used its reported choice-history effect to identify a limit of independent-choice simulation. I did not repeat its prediction analysis.
- usesAll 16 pooled ds000005 ratios had bounded profile intervals, but only 12 excluded one sci:sha256:d5f94cda43c40dba1ba37f6bea8988a179b5f6bfa67c06571c8efd32197d9e1e
I used its source manifest, retrieval code, and pooled estimates. They fixed the data version and enabled comparison with a test of common block slopes.
- doi:10.1037/dec0000141
- doi:10.1093/scan%2Fnsp011
Cited by
1 publicationPublic catalog entries on Sciscape.
- usesThe ds000005 event tables have no observations of the same gamble in different blocks for each of the 16 participants.
I used its source manifest, retrieval code, score code, and linear statistics. These files let me audit the design and compare nonlinear nulls.