**HLM Example-Simple Example**

Example from,
*Woltman, Feldstain, MacKay, Rocchi (2012). An
introduction to hierarchical linear modeling. Tutorial in Quantitative Methods
for Psychology, 8(1), 52-69.*

*30 basketball teams, 10 players per team
Three variables = Life satisfaction (outcome), shots, coach years of experience*

*Software (free student version):
http://www.ssicentral.com/hlm/downloads.html*

**Data Condition**

*Unconstrained (null) Model*

**One-way ANOVA**

*Results:
Confirms that variability in outcome, by level 2 group, is different from 0.0.
ICC = 14.96/(14.96+14.61) = .51 (51% of the variance in outcome is at the group
level (quite large)*

*Random Intercepts Model*

*Note: Group center Shots_on & click on
u1*

Results:

*Effect size (r2) = (14.61-4.6)/14.61 = .715 [note that 14.61 came from
the null model]*

*Confirms that variability in outcome and slope, by level 2 group, is
different from 0.0.*

*Means as Outcomes Model*

Note: COACH_EX is grand-mean centered

*Results:*

*Effect size (r2) = (14.61-1.68)/14.61 = .888 [note that 14.61 came from
the null model]
Coaching experience explains 88.8% between variance in life satisfaction*

*Random Intercepts and Slopes Model*