Table 1.
Overview of the Regression Parameter Estimates for the Main Parameters, Alpha (α) and Bèta (β), of the Individual Sigmoid Maximum Likelihood Fits.
| Parameter | Estimate (SE) | P(χ2) | 95% CI |
|---|---|---|---|
| Alpha (α) | |||
| Intercept | 28.13 (.92) | 2.00 × 10−16 | [26.33, 29.93] |
| Presentation mode | 5.19 (1.19) | 2.41 × 10−5 | [2.86, 7.52] |
| Level of categorization | −1.88 (.66) | 5.11 × 10−3 | [−3.17, −.59] |
| Bèta (β) | |||
| Intercept | 8.91 (.49) | 2.00 × 10−16 | [8.42, 9.87] |
| Presentation mode | −2.19 (.67) | 1.25 × 10−3 | [−3.50, −.88] |
| Level of categorization | −.88 (.67) | 1.90 × 10−1 | [−2.19, .43] |
Note. These provided an overall estimation of the time-dependent categorization performance in each test session per participant and were used separately as DV in a General Linear Modeling (GLMM) approach (McCullagh, 1984).