Longitudinal Data Analysis
Social Science Researchers


Software for the analysis and management of longitudinal data

This page includes notes on some of the software packages which we use or make reference to within the materials of the 'Longitudinal Data Analysis' course. It is not comprehensive - other packages may also be appropriate for the same exercises.


General purpose packages with capabilities for longitudinal data

SPSS / LDA SPSS support

In the UK social sciences, SPSS is probably the most widely used generalist package covering both data management and data analysis operations. Its functionality incorporates both introductory and more advanced tasks over a vast range of operations. It has particularly extended materials suited to the introductory level user. However, only a relatively small proportion of its capacity is oriented around the use of specifically longitudinal data resources.

An extended collection of training resources in the use of SPSS for longitudinal analysis - including guidance texts, an introductory training course, and example exercises demonstrating longitudinal techniques - are available within the Longitudinal Data Analysis Web site.


STATA / LDA Stata support

Stata is a popular generalist package for both data management and data analysis operations. It is widely used in academic social science in the US, and is increasingly popular in the UK. Its functionality includes both fairly basic and highly advanced forms of data management and data analysis. In particular, it incorporates extensive suites of commands specifically designed for longitudinal analysis strategies.

An extended collection of training resources in the use of STATA for longitudinal analysis - such as guidance texts, links, and example exercises - are available within the Longitudinal Data Analysis Web site.



R is a freeware package with an extremely wide range of capabilities, including a capacity for many of the highly advanced model formulations which can ultimately be necessary for complex social science datasets. However, it is not an introductory package - its successful use requires a fairly high level of existing skill in the field.

Specialist packages suited to longitudinal analyses

SABRE (Software for the Analysis of Binary Recurrent Events) is a freeware package designed for the analysis of binary, ordinal and count 'recurrent events' - eg panel data with a categorical outcome measure. It has certain modelling features which go beyond those available in STATA. It is particularly appropriate for the analysis of work and life histories, and has been used intensively on many longitudinal datasets. Its development has been funded by the ESRC and Lancaster University.

The MLwiN package can be purchased via the Centre for Multilevel Modelling. 'Multilevel models' utilise estimators for hierarchical random effects which are often used in a longitudinal context (ie, repeated measures or repeated events as clustered within individual cases).


TDA ('Transitions Data Analysis') is a freeware package designed for event history analyses. It is extensively illustrated in the textbook: Blossfeld and Rohwer (2002) 'Techniques of Event History Analysis', NJ: Lawrence Erlbaum.


GLLAMM (Generalised Linear Latent and Mixed Models) is an extension routine for STATA. GLLAMM allows for the estimation of a wide range of longitudinal models.


M-Plus is one of a number of software packages with a capacity for a range of complex structural equation models. Such models are increasingly being used to analyse data with a longitudinal component.


Other Software guidance materials


The PEAS (Practical Examplars in the Analysis of Surveys) project incorporates extended training materials in using 4 major statistical analysis packages - SPSS, STATA, R and SAS - for a variety of survey analysis operations. It incorporates introductory guides and command file examplar exercises in the packages.

UCLA statistical computing guide

UCLA's front page offering guidance on different statistical software packages, leading to extended details on many programmes including Stata and SPSS.