Table 3.

Generalized Linear Mixed Model (GLMM) – Modelling Weekly Sleep Quality and Twitter Use for Freshmen Students.

Section A: Tweeting Time of Day
	Time of Day (Proportion of Weekly Tweets that are:)	B	SE	AIC	BIC
Weekdays1	Morning	0	0.111	3177	3269
	Afternoon	−0.12	0.102	3175	3268
	Evening	0.189*	0.097	3173	3266
	Late Night	−.937**	0.352	3167	3260
Weekends1	Morning	0.167	0.135	3175	3268
	Afternoon	−0.186	0.111	3174	3267
	Evening	0.1	0.116	3176	3269
	Late Night	−0.342	0.342	3173	3266
Section B: Characteristics of Weekday Tweets		B	SE	AIC	BIC
	Short Tweets
Proportion of tweets during each time period that are short1:	Morning	0.017	0.084	3177	3270
	Afternoon	0.041	0.082	3177	3270
	Evening	−0.117	0.08	3175	3268
	Late night	−.413**	0.139	3167	3260
	Long Tweets
Proportion of tweets during each time period that are long1:	Morning	0.066	0.08	3177	3269
	Afternoon	−0.024	0.08	3177	3270
	Evening	.197*	0.087	3172	3265
	Late night	−0.025	0.137	3176	3269
	Emotions
Proportion of tweets that are a given emotion2:	Angry	−0.205	0.169	3013	3106
	Fearful	−0.302*	0.131	3011	3102
	Loving	0.026	0.138	3016	3108
	Joyful	0.105	0.128	3015	3107
	Neutral	−0.135	0.131	3015	3107

¹: Total Number of Observations: 1,295, Total Number of Individuals: 166

²: Total Number of Observations: 1,229, Total Number of Individuals: 165

^*P < 0.05,

^**P < 0.01