Analyzing State Sequences with Probabilistic Suffix Trees: The PST R Package

This article presents the PST R package for categorical sequence analysis with probabilistic suffix trees (PSTs), i.e., structures that store variable-length Markov chains (VLMCs). VLMCs allow to model high-order dependencies in categorical sequences with parsimonious models based on simple estimation procedures. The package is specifically adapted to the field of social sciences, as it allows for VLMC models to be learned from sets of individual sequences possibly containing missing values; in addition, the package is extended to account for case weights. This article describes how a VLMC model is learned from one or more categorical sequences and stored in a PST. The PST can then be used for sequence prediction, i.e., to assign a probability to whole observed or artificial sequences. This feature supports data mining applications such as the extraction of typical patterns and outliers. This article also introduces original visualization tools for both the model and the outcomes of sequence prediction. Other features such as functions for pattern mining and artificial sequence generation are described as well. The PST package also allows for the computation of probabilistic divergence between two models and the fitting of segmented VLMCs, where sub-models fitted to distinct strata of the learning sample are stored in a single PST

Analyzing and Visualizing State Sequences in R with TraMineR

This article describes the many capabilities offered by the TraMineR toolbox for categorical sequence data. It focuses more specifically on the analysis and rendering of state sequences. Addressed features include the description of sets of sequences by means of transversal aggregated views, the computation of longitudinal characteristics of individual sequences and the measure of pairwise dissimilarities. Special emphasis is put on the multiple ways of visualizing sequences. The core element of the package is the state se- quence object in which we store the set of sequences together with attributes such as the alphabet, state labels and the color palette. The functions can then easily retrieve this information to ensure presentation homogeneity across all printed and graphical displays. The article also demonstrates how TraMineRâÂÂs outcomes give access to advanced analyses such as clustering and statistical modeling of sequence data.

Analyzing and Visualizing State Sequences in R with TraMineR

This article describes the many capabilities offered by the TraMineR toolbox for categorical sequence data. It focuses more specifically on the analysis and rendering of state sequences. Addressed features include the description of sets of sequences by means of transversal aggregated views, the computation of longitudinal characteristics of individual sequences and the measure of pairwise dissimilarities. Special emphasis is put on the multiple ways of visualizing sequences. The core element of the package is the state se- quence object in which we store the set of sequences together with attributes such as the alphabet, state labels and the color palette. The functions can then easily retrieve this information to ensure presentation homogeneity across all printed and graphical displays. The article also demonstrates how TraMineR’s outcomes give access to advanced analyses such as clustering and statistical modeling of sequence data

The Swiss Household Panel 1999-2003: data for research on micro-social change

"Die Umfrage Leben in der Schweiz des Schweizer Haushalt Panels (SHP) bietet eine einzigartige longitudinale Datenbasis an. 1999 wurden 7.799 Personen von 5.074 Haushalten über ihre Lebensbedingungen befragt. Sämtliche 14-jährigen und älteren Personen, die in diesen Haushalten wohnen, sollen fortan während zehn bis fünfzehn Jahren in jährlichem Abstand befragt werden. Die Erhebung wird mittels computerunterstützten Telefoninterviews (CATI: Computer Assisted Telephone Interviewing) durchgeführt. Mittlerweile konnten die ersten zwei Befragungswellen erfolgreich realisiert werden. Anders als bei den vorwiegend auf sozioökonomischen Bedingungen ausgerichteten Panels - wie dem SOEP in Deutschland und dem BHPS in England - deckt das SHP ein breites Spektrum von Themen und sozialwissenschaftlichen Forschungsansätzen ab. Das Faktenmaterial wird ergänzt durch 'subjektive' Beurteilungen. Die Trägerschaft des SHPs besteht aus dem Schwerpunktprogramm SPP 'Zukunft Schweiz', dem Bundesamt für Statistik und der Universität Neuchâtel." (Autorenreferat)"The Living in Switzerland survey of the Swiss Household Panel (SHP) provides a unique longitudinal database in Switzerland. In 1999, 7,799 members of 5,074 households – from a stratified random sample of the permanent resident population of Switzerland – were interviewed about their living conditions. All household members aged 14 years and older are to be interviewed annually for 10 to 15 years. The SHP survey is conducted using computer-assisted telephone interviewing (CATI). To date, the first two waves have been carried out successfully. In comparison with panels such as the SOEP in Germany and the BHPS in Britain concentrating on socio-economic conditions, the SHP covers a broader range of topics and approaches in the social sciences. Subjective assessments complement the factual information. The SHP is a joint project run by the Swiss Priority Programme (SPP) 'Switzerland towards the Future', the Swiss Federal Statistical Office and the University of Neuchâtel." (author's abstract

Transitions dans le parcours de vie et construction des inégalités

Tout au long de leur existence, les individus suivent des chemins singuliers dont les trajectoires ne sont pas le simple fait de la seule volonté ou du hasard. Ces cheminements se révèlent souvent générateurs d'inégalités entre individus, notamment au cours des transitions des âges de la vie (enfance, adolescence, âge adulte, grand âge), ou lors de différentes étapes (mariage, divorce, deuil, etc). C'est afin de mieux comprendre les modalités et les combinaisons d'influence à l'origine des inégalités dans les parcours de vie, que les éditeurs de cet ouvrage ont réuni des chercheurs issus des sciences psychologiques, sociales et économiques, afin de croiser leurs regards sur la manière dont ces inégalités se creusent ou se réduisent au fil des trajectoires. Cet ouvrage interdisciplinaire met en relief la richesse d'une approche des inégalités dans la perspective dynamique du parcours de vie.Peer reviewe

Methods for the analysis of life trajectories and their applications

This PhD thesis presents methods for the analysis of life course data in demography and social sciences. Their focus is the analysis of categorical sequences representing life trajectories, that is, series of statuses or roles that an individual enacts over time in domains such as education, family or work. The presented methods aim to discover, describe and explain life course patterns. A first contribution is anchored in the main existing framework for sequence analysis, based on the computation of pairwise dissimilarities between sequences. It addresses the issue of summarizing sets of life trajectories with typical patterns. The second contribution proposes a general framework for analyzing life trajectories that is based on a particular class of markovian models called variable length Markov chains