Statistical Methods

Multilevel Modeling Guide

Run hierarchical linear models for nested psychology data — schools, therapists, families

multilevel modeling HLM lme4 ICC

¥29.99

276 researchers installed this

5.0(1)

About this skill

What it does

Guides psychology researchers through multilevel modeling (HLM/MLM) for data with nested structures.

Common applications

Students nested within classrooms or schools
Clients nested within therapists
Measurements nested within individuals (longitudinal)
Family members nested within families
Participants from multiple sites

Workflow steps

ICC calculation — is MLM even necessary?
Model building strategy — unconditional, random intercepts, random slopes
Centering decisions — group-mean vs. grand-mean centering
Level-1 and Level-2 predictors — what goes where and why
Cross-level interactions — specifying and interpreting
Software code: R (lme4/nlme), HLM 8, Mplus, SPSS Mixed
Results reporting: fixed effects table, variance components, ICC

Interpretation prompts

Paste your model output and get a plain-language interpretation ready for your Results section.

Ideal for

Clinical, developmental, educational, and health psychology with any nested data structure.

What researchers say

5.0(1)

陈思雨香港中文大学博士后 · CUHK Postdoc, Education Policy

Multilevel modeling was the biggest challenge in my postdoc research on school effects. This skill helped me specify the correct random effects structure for my three-level model (students within classes within schools) and write up ICC values and model comparisons properly.