Table 2.
Two-Level Hierarchical Generalized Linear Model of Recall Performance Predicted by Item Value, List, and Participant Age
| Fixed effects | Coefficient: Experiment 1 | Coefficient: Experiment 2 |
|---|---|---|
| Intercept (β00) | −0.20 | −0.58*** |
| Predictors of intercept | ||
| Age (person-level) (β01) | 0.41* | 0.54** |
| Value (β10) | 0.17*** | 0.28*** |
| Predictors of value | ||
| Age (β11) | 0.02 | −0.001 |
| List (β20) | 0.08 | −0.36*** |
| Predictors of list | ||
| Age (β21) | −0.31*** | 0.08 |
| List × Value (β30) | 0.10*** | 0.11*** |
| Predictors of List × Value | ||
| Age (β31) | −0.04 | −0.02 |
| Random effects | Variance | Variance |
| Intercept (person-level) (r 0) | 0.16*** | 0.31*** |
| Value (r 1) | 0.02*** | 0.04*** |
Notes. The dependent variable is recall performance coded as 0 (not recalled) or 1 (recalled). Logit link function was used to address the binary dependent variable. Level 1 models were of the form ηij = π0j + π1j (Value) + π2j (List) + π3j (List × Value). Level 2 models were of the form π0j = β00 + β01 (Age) + r 0j, π1j = β10 + β11 (Age) + r 1j, π2j = β20 + β21 (Age), π3j = β30 + β31 (Age).
*p < .05. **p < .01. ***p < .001.