Table 9.
Fixed-effect estimates for model of pupillary responses from 0 to 5.8 seconds time-locked to babble masker onset to examine the effect of SNR and age group (observations = 96,612, groups: participant x SNR = 332, participant = 63)
| Fixed Effect | Estimate | SE | 95% CI | t | p |
|---|---|---|---|---|---|
|
| |||||
| Intercept | 7.26 | 1.26 | [ 4.79, 9.73] | 5.76 | < .001 |
| otl | 48.14 | 10.62 | [ 27.33, 68.94] | 4.53 | < .001 |
| ot2 | −30.44 | 6.90 | [−43.96, −16.92] | −4.41 | < .001 |
| SNR 0 | −0.43 | 1.80 | [ −3.95, 3.09] | −0.24 | 0.811 |
| SNR 5 | −3.45 | 1.80 | [ −6.98, 0.07] | −1.92 | 0.055 |
| SNR 10 | −3.53 | 1.80 | [ −7.06, −0.01] | −1.96 | 0.049 |
| SNR 15 | −3.72 | 1.77 | [ −7.19, −0.25] | −2.10 | 0.035 |
| SNR 20 | −2.32 | 1.80 | [ −5.85, 1.20] | −1.29 | 0.197 |
| ot1 x SNR 0 | 44.77 | 14.58 | [ 16.19, 73.34] | 3.07 | 0.002 |
| ot1 x SNR 5 | 7.21 | 14.59 | [−21.39, 35.81] | 0.49 | 0.621 |
| ot1 x SNR 10 | −11.30 | 14.59 | [−39.90, 17.30] | −0.77 | 0.439 |
| ot1 x SNR 15 | −16.19 | 14.34 | [−44.29, 11.92] | −1.13 | 0.259 |
| ot1 x SNR 20 | −13.08 | 14.58 | [−41.65, 15.50] | −0.90 | 0.370 |
| ot2 x SNR 0 | 44.88 | 9.26 | [ 26.73, 63.02] | 4.85 | < .001 |
| ot2 x SNR 5 | 61.77 | 9.27 | [ 43.60, 79.94] | 6.66 | < .001 |
| ot2 x SNR 10 | 26.06 | 9.27 | [ 7.88, 44.23] | 2.81 | 0.005 |
| ot2 x SNR 15 | 14.74 | 9.11 | [ −3.11, 32.59] | 1.62 | 0.105 |
| ot2 x SNR 20 | 20.07 | 9.26 | [ 1.92, 38.22] | 2.17 | 0.030 |
| Group (MA vs. YA) | 1.03 | 1.85 | [ −2.60, 4.65] | 0.55 | 0.579 |
| Group x SNR 0 | 1.53 | 2.64 | [ −3.65, 6.70] | 0.58 | 0.564 |
| Group x SNR 5 | 1.87 | 2.63 | [ −3.28, 7.02] | 0.71 | 0.476 |
| Group x SNR 10 | −4.82e-03 | 2.60 | [ −5.10, 5.10] | −1.85e-03 | 0.999 |
| Group x SNR 15 | −1.26 | 2.62 | [ −6.39, 3.88] | −0.48 | 0.632 |
| Group x SNR 20 | −1.26 | 2.64 | [ −6.44, 3.91] | −0.48 | 0.632 |
| ot1x Group | −4.37 | 15.56 | [−34.87, 26.14] | −0.28 | 0.779 |
| ot1 x Group x SNR 0 | 13.71 | 21.46 | [−28.35, 55.77] | 0.64 | 0.523 |
| ot1 x Group x SNR 5 | 32.89 | 21.35 | [ −8.94, 74.73] | 1.54 | 0.123 |
| ot1 x Group x SNR 10 | 24.20 | 21.16 | [−17.26, 65.66] | 1.14 | 0.253 |
| ot1 x Group x SNR 15 | 15.46 | 21.28 | [−26.25, 57.18] | 0.73 | 0.468 |
| ot1 x Group x SNR 20 | 8.97 | 21.45 | [−33.07, 51.00] | 0.42 | 0.676 |
| ot2 x Group | −4.89 | 10.11 | [−24.70, 14.92] | −0.48 | 0.628 |
| ot2 x Group x SNR 0 | 3.18 | 13.65 | [−23.57, 29.93] | 0.23 | 0.816 |
| ot2 x Group x SNR 5 | −11.65 | 13.57 | [−38.26, 14.96] | −0.86 | 0.391 |
| ot2 x Group x SNR 10 | 16.76 | 13.46 | [ −9.62, 43.13] | 1.24 | 0.213 |
| ot2 x Group x SNR 15 | 14.82 | 13.53 | [−11.70, 41.35] | 1.10 | 0.273 |
| ot2 x Group x SNR 20 | 12.19 | 13.63 | [−14.54, 38.91] | 0.89 | 0.371 |
Growth curve formula: lmer(Pupil ~ (ot1 + ot2)*Group*SNR + (0 + ot1 + ot2 | participant) + (ot1 + ot2 | participant:SNR), control = lmerControl(optimizer = ‘bobyqa’), REML = FALSE). Orthogonal polynomial terms: ot1 = linear (slope); ot2 = quadratic (curvature).