Table 2.
Model selection for PRLT performance in the two-groups sample
Model | Fixed factors | df | AIC | χ2 | p |
---|---|---|---|---|---|
Sat. (0.a) | Group, Phase, Log-trial, 2-way interactions, 3-way interaction | 19 | 10,422 | ||
1 | Saturated minus 3-way interaction | 16 | 10,419 | 2.418 |
0.490 (1 ≥ 0.a) |
2.1 | Model 1 minus Group × Log-trial | 15 | 10,418 | 1.418 |
0.227 (2.1 ≥ 1) |
2.2b | Model 1 minus Phase × Log-trial | 13 | 10,432 | 18.978 |
< 0.001 (1 > 2.2) |
2.3 | Model 1 minus Phase × Group | 13 | 10,418 | 4.973 |
0.174 (2.3 ≥ 1) |
2.4 | Model 1 minus Group × Log-trial and Phase × Group | 12 | 10,417 | ||
3a | Model 2.4 minus Group | 11 | 10,416 | 0.592 |
0.459 (3 ≥ 2.4) |
Significant p values are in italics
aBest fitting model
bAlmost singular fit (given the risk of overfitting, parameters will be estimated both for Model 1 and Model 3) (Although singular models are statistically well defined, singular fits may correspond to overfitted models with low power, and inferential procedures such as likelihood ratio tests may be inappropriate. In our case, singularity is due to the inclusion of Log-trial as a random slope in the model. Although it is theoretically sensible to assume that there are random individual differences in learning rates across participants, random slopes are not necessary to capture statistical dependency between repeated measures and thus to properly estimate within-participant effects. In view of that, and for the sake of consistency, alternative analyses without random slopes in the models are provided in the Additional file)
Sat Saturated