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Idiographic Data Analysis: Quantitative Methods—From Simple to Advanced

  • Ellen L. Hamaker
  • Conor V. Dolan
Chapter

Abstract

Time series analysis is a technique which can be used to model a large number of repeated measurements taken from a single case. This makes it a valuable approach for social scientists who are interested in idiographic data analysis. A fundamental time series model is the autoregressive moving average (ARMA) model. In this chapter we introduce the reader to the ARMA model and several extensions of it, including nonstationary models, multivariate models and nonlinear models. The focus is on the utility of these techniques for social scientists and we discuss existing applications within the social sciences to illustrate this. In the discussion we indicate how these techniques can be extended to handle multiple cases, and we briefly touch upon some valuable time series techniques which could not be treated in the current chapter.

Keywords

ARMA Model ARIMA Model Deterministic Trend White Noise Sequence Move Average Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This work was supported by the Netherlands Organization for Scientific Research (NWO), VENI grant 451–05–012 awarded to Ellen L. Hamaker.

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Methods and Statistics Faculty of Social SciencesUtrecht UniversityUtrechtThe Netherland

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