Table 2 GLMM analysis results.

From: Aberrant neural processing of event boundaries in persons with Parkinson’s disease

Formula: segmentation ~ 1 + proportion * group * movie + (1 + proportion + movie || subject)

Term

b

SE

z

p

Intercept

 − 3.56

0.13

 − 26.95

 < 0.001

Proportion

0.51

0.03

14.99

 < 0.001

Group

0.23

0.26

0.89

0.373

Movie: BF-GA

0.67

0.10

6.51

 < 0.001

Movie: PA-BF

 − 0.51

0.09

 − 5.62

 < 0.001

Proportion * group

0.22

0.07

3.23

0.001

Proportion * movie: BF-GA

 − 0.23

0.05

 − 5.29

 < 0.001

Proportion * movie: PA-BF

0.14

0.04

3.42

 < 0.001

Group * movie: BF-GA

 − 0.18

0.19

 − 0.95

0.343

Group * movie: PA-BF

0.12

0.17

0.73

0.464

Proportion * movie: BF-GA * Group

0.07

0.09

0.82

0.415

Proportion * movie: PA-BF * Group

 − 0.09

0.08

 − 1.07

0.286

Variance components (SD)

Goodness of fit

  

Intercept

0.34 (0.59)

Log Likelihood: -7160.3

  

Proportion

0.04 (0.19)

REML deviance: 14320.7

  

Movie: GA

0.47 (0.68)

   

Movie: BF

0.23 (0.48)

   

Movie: PA

0.59 (0.77)

   
  1. The dependent variable “segmentation” (see Formula) refers to the individual segmentation pattern of each subject. BF “preparing breakfast”, GA “working in the garden”, PA “preparing a party”.
Back to article page