Resources for using MLwiN

Over the years the team has written a large number of resources for using MLwiN. While there is a rolling program of updating, inevitably some materials lag behind others. This page is meant to point you where to look for further help in using MLwiN to estimate models. It gives an overview of our materials.

Where there are multiple entries for a topic, we have tried to put the most introductory first, followed by the most comprehensive; the most technical comes at the end.

The resources

USER: Rasbash, J., Steele, F., Browne, W.J. and Goldstein, H. (2017) A User's Guide to MLwiN, v3.00 (PDF, 4,395kB), Centre for Multilevel Modelling, University of Bristol.

MCMC: Browne, W.J. (2017) MCMC Estimation in MLwiN, v3.00 (PDF, 6,430kB), Centre for Multilevel Modelling, University of Bristol.

SUPP: Rasbash, J., Charlton, C., Jones, K. and Pillinger, R. (2017) Manual Supplement to MLwiN, v3.00 (PDF, 1,931kB), Centre for Multilevel Modelling, University of Bristol.

COMMAND: Rasbash, J., Browne, W.J. and Goldstein, H. (2003) MLwiN 2.0 Command Manual (PDF, 880kB), Centre for Multilevel Modelling, University of Bristol.

FAQ: CMM software support Frequently Asked Questions

LEMMA: Multilevel modelling online course

REALCOM: Developing multilevel models for REAListically COMplex social science data

C&Hvol1: Jones, K and Subramanian, V S (2014) Developing multilevel models for analysing contextuality, heterogeneity and change using MLwiN, Volume 1 , University of Bristol.

C&Hvol2: Jones, K and Subramanian, V S (2013) Developing multilevel models for analysing contextuality, heterogeneity and change using MLwiN, Volume 2, University of Bristol.

Gallery: the Multilevel Gallery which is a database of (mostly) published journal articles which fit multilevel models. It is searchable by model type and substantive area.

TEXT: MLwiN Textbook Examples provided by UCLA Statistical Consulting Group

Other sources of help

This is a guide to all the materials that CMM have, for further assistance:

  • All users can post enquiries to the MLwiN user forum
  • If you have bought MLwiN, you may be entitled to email support. (If you are a UK academic and have downloaded the free version, unfortunately, you are not entitled to free support.)
  • You can also join the JISC Multilevel Modelling discussion list which is a general discussion list that is not run by CMM.

Multilevel modelling: the background

Structures and classifications Structures
Lemma Module 4
What types of model can be fitted in MLwiN? Types
Basic concepts behind the models USER: Chapter 1
Research questions and data Lemma Module 8
Single level multiple regression models Lemma Module 3
The basic two-level model Lemma Module 5
Web resources for multilevel modelling Links to non-CMM resources
Getting started with MLwiN (without modelling) C&Hvol1: Chapter 2

Hierarchical normal-theory models

Two-level hierarchical model with a continuous response

The basic models Lemma Module 5
USER: Chapter 2
Residuals USER: Chapter 3
Slides with voiceover
Random intercepts and random slopes USER: Chapter 4
Slides; slides with voiceover
Customised (AKA out of sample) predictions SUPP: Chapter 2 and Appendix A
Comparing a sequence of models &testing C&Hvol1: Chapter 6
SUPP: Chapter 4
Diagnostics USER: Chapter 15
C&Hvol1: Chapter 4
Variance functions USER: Chapter 7
Power point slides: introduction to multilevel models Slides
Multilevel Statistical Models by Harvey Goldstein MSM Script
Intro Multilevel Modelling, by Kreft and de Leeuw IMM Script
Multilevel modelling by Snijders and Bosker B&Adv Script
2nd edition

Contextual variables at level two

Contextual effects and cross-level interactions USER: Chapter 6
C&Hvol1: Chapter 8
Customised predictions plot SUPP: Chapter 2 and Appendix A

Going further with the basic model

Partitioning variance VPC
Estimation by MCMC C&Hvol1: Chapter 10
MCMC: Chapter 1 to 6
Complex heterogeneity at level 1 with MCMC MCMC: Chapter 9
Robust or sandwich errors FAQRobust
FAQ's ICC FAQICC
FAQ's residuals FAQ Res
Survey weights FAQWts

Three-level models

Concepts Lemma Module 4
Specification, estimation, interpretation Lemma Module 11
Repeated cross-sectional model C&Hvol1: Chapter 11

Models with multiple responses (including multivariate and panel models)

Multivariate response models

Concepts Lemma Module 4
Multivariate normal response models USER: Chapter 14
Estimation in MCMC MCMC: Chapter 18
Customised predictions SUPP: Chapter 2.5 and Appendix A
Estimation in MCMC MCMC: Chapter 18

Repeated measures (panel models)

Concepts C&Hvol2: Chapter 14; Lemma Module 15
Models for repeated measures USER: Chapter 13; Lemma Module 15
Presentation Multilevel models for longitudinal data (PDF, 370kB)
Application Physical Health functioning (PDF, 933kB)
Modelling longitudinal and cross-sectional effects C&Hvol2: Chapter 15
Applied Longitudinal by Singer and Willett ALDA Script
Ordinal categories for time SUPP: Chapter 2
Auto-correlated errors in continuous time SUPP: Chapter 5
As a multivariate model MCMC: Chapter 18
With autoregressive structure MCMC: Chapter 18
FAQ's Longitudinal data FAQs
Event history Multilevel discrete-time event history

Multilevel factor analysis

Estimation in MCMC MCMC: Chapter 20
Multilevel structural equation models REALCOM

Discrete outcomes

Bernoulli or binomial responses: binary or proportions

Concepts Lemma Modules 6 & 7
Quasi-likelihood estimation USER: Chapter 9
Modelling proportions (binomial counts) USER: Chapter 9.5
C&Hvol2: Chapter 12
MCMC estimation MCMC: Chapter 10
Customised predictions SUPP: Chapter 2.2 and Appendix A
Comparing a sequence of models SUPP: Chapter 4
Partitioning variance VPC
PowerPoint presentation on discrete models Slides
Applications Multilevel Gallery
FAQ's Discrete FAQ's
Modelling segregation Modelling ethnic segregation using MLwiN (PDF, 972kB)

Nominal responses: multiple categories unordered

Concepts Lemma Module 10
Quasi-likelihood estimation USER: Chapter 10
MCMC estimation MCMC: Chapter 12
Customised predictions SUPP: Chapter 2.3 and Appendix A
Comparing a sequence of models SUPP: Chapter 4
PowerPoint presentation Slides
Applications Multilevel Gallery
FAQ's Discrete FAQ's
Modelling segregation Modelling ethnic segregation using MLwiN (PDF, 972kB)

Ordinal responses: multiple categories ordered

Concepts Lemma Module 9
Quasi-likelihood estimation USER: Chapter 11
MCMC estimation MCMC: Chapter 13
Customised predictions SUPP: Chapter 2.3 and Appendix A
Comparing a sequence of models SUPP: Chapter 4
Powerpoint presentation Slides
Applications Multilevel Gallery
FAQ's Discrete FAQ's

Poisson and Negative Binomial Models: counts and rates

Concepts C&Hvol2: Chapter 13
Quasi-likelihood estimation USER: Chapter 12
MCMC estimation MCMC: Chapter 11
Customised predictions SUPP: Chapter 2.4 and Appendix A
Comparing a sequence of models SUPP: Chapter 4
Powerpoint presentation Slides
Applications Multilevel Gallery
FAQ's Discrete FAQ's

Multivariate mixed response models

Discrete & continuous outcomes simultaneously MCMC: Chapter 18
Estimation in REALCOM REALCOM
Responses at more than one level & of different type REALCOM
Stat – JR to come (Hugh is there a Link?)

Non-Hierarchical models

Cross- classified models

Concepts Lemma Module 4
Lemma Module 12
Estimation in MCMC MCMC: Chapter 15
Comparing a sequence of models SUPP: Chapter 4
Applications Multilevel Gallery

Multiple membership models

Concepts Lemma Module 4
Lemma Module 13
Estimation in MCMC MCMC: Chapter 16
Comparing a sequence of models SUPP: Chapter 4
Applications Multilevel Gallery

Spatial models

Concepts C&Hvol2: Chapter 16
Estimation in MCMC MCMC: Chapter 17
Space-time models C&Hvol2: Chapter 16

Estimation

IGLS (maximum likelihood estimation) algorithm

Underlying concepts C&Hvol1: Chapter 9
Commands for the IGLS algorithm COMMAND: Chapter 13
Constraining parameters FAQ Constraint

MCMC estimation

Bayesian approach and MCMC estimation MCMC: Chapter 1
C&Hvol1: Chapter 10
Fixed and random effects estimated by MCMC MCMC: Chapter 3.3
Simulation in MLwiN USER: Chapter 16
Gibbs sampling for MCMC and DIC MCMC: Chapter 1 to 3
Metropolis Hastings sampling MCMC: Chapter 1 to 4
Using prior distributions MCMC: Chapter 5
Speeding up (less correlated chains) MCMC: Chapter 21-c25
Speeding up (less correlated chains) C&Hvol1: Chapter 10 and C&Hvol2: Chapter 12
MCMC FAQs FAQ MCMC
Commands for MCMC estimation COMMAND: Chapter 16

Bootstrap estimation

Iterated and non-parametric bootstrap USER: Chapter 16

Estimates of residuals and shrinkage

Fix e d and random effects USER: Chapter 2
C&Hvol1: Chapter 2
Residuals and shrinkage USER: Chapter 9

Data and design

Missing data

Concepts Lemma Module 14
http://www.missingdata.org.uk
Estimation in MCMC MCMC: Chapter 18
Multiple imputation in REALCOM REALCOM
Multiple imputation in Stat-JR Multiple imputation for 2-level models in Stat-JR
Getting data in (with missing) FAQ data in
Identifying patterns of missingness FAQ Pat Miss (PDF, 381kB)

Measurement error

Measurements error and misclassification MCMC: Chapter 14
Measurement error modelling REALCOM

Power calculations

Concepts FAQ Power
Sample size Size
Concepts and software MLPowSim

MLwiN functioning

Data and worksheets

Chapter 2

Research questions and data Lemma Module 8
Getting started with data USER: Chapter 8
Viewing data SUPP: Chapter 8
Getting started with MLwiN (without modelling) C&Hvol1:
Getting data in to MLwiN FAQ data in
Getting data out of MLwiN FAQ dataout
Understanding worksheets C&Hvol1: Chapter 2
Increasing worksheet size FAQ Inc Size
Large data sets FAQ Large
Getting data from other software SUPP: Chapter 6
Minitab, Stata and SPSS FAQ Other packages
Categorical variables reference categories SUPP: Chapter 8 & 1
FAQ Categ
Categorical variables: ordinal categories SUPP: Chapter 2
Combining categorical columns SUPP: Chapter 8
Finding unique codes SUPP: Chapter 8

Graphs

Graphs USER: Chapter 5
Graphs of residuals USER: Chapter 3
Graphs of group lines USER: Chapter 4
High- resolution graphics C&Hvol1: Chapter 2
http://www.gigasoft.com/
Customised predictions plot SUPP: Chapter 2 and Appendix A
3D graphs SUPP: Chapter 3

Simulation studies

Simulation USER: Chapter 16
Running a simulation study MCMC: Chapter 8
Commands for simulation COMMAND: Chapter 20

Commands, syntax and macros

Guide to using syntax C&Hvol1: Chapter 1
COMMAND: Chapter 1
Quick reference sheet for commands Command dictionary (PDF, 47kB)
Quick introduction to commands and macros Introduction to commands (PDF, 33kB)
FAQ on commands FAQ syntax
An example of a macro C&Hvol1: Chapter 1
Macro commands COMMAND: Chapter 15
Macro programming SUPP: Chapter 4
FAQ on macros FAQ macro
Stored estimates FAQ estimates
Every documented command COMMAND
more recent commands SUPP: all chapters
Commands for the IGLS algorithm COMMAND: Chapter 13
Commands for MCMC estimation COMMAND: Chapter 16

MLwiN and different operating systems

MLwiN system requirements Frequently Asked Questions
Mac, server etc Frequently Asked Questions

MLwiN Bugs and errors

Bugs and errors during estimation FAQ errors in estimation
Implausible results FAQ errors in estimation
Problems opening worksheets FAQ crashes

Interoperability: using MLwiN with other software

Stata runmlwin: MLwiN from within Stata
R R2MLwiN: MLwiN from within R
Stat-JR Stat-JR: a software environment
MLwiN to WinBUGS MCMC: Chapter 7

Other software and how it can be used with CMM materials

LEMMA training material in Stata LEMMA
LEMMA training material in R LEMMA
LEMMA training material in SPSS LEMMA
Examples of other multilevel software
(some of these are out of date)
CMM software reviews

Further training and information

Face to face workshops Workshops
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