Book contents
- Frontmatter
- Contents
- Figures
- Preface
- 1 Introduction to Observational Methods
- 2 Coding Schemes and Observational Measurement
- 3 Recording Observational Data
- 4 Representing Observational Data
- 5 Observer Agreement and Cohen’s Kappa
- 6 Kappas for Point-by-Point Agreement
- 7 The Intraclass Correlation Coefficient (ICC) for Summary Measures
- 8 Summary Statistics for Individual Codes
- 9 Cell and Summary Statistics for Contingency Tables
- 10 Preparing for Sequential and Other Analyses
- 11 Time-Window and Log-Linear Sequential Analysis
- 12 Recurrence Analysis and Permutation Tests
- Epilogue
- Appendix A Expected Values for Kappa Comparing Two Observers
- Appendix B Expected Values for Kappa Comparing with a Gold Standard
- References
- Index
11 - Time-Window and Log-Linear Sequential Analysis
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Figures
- Preface
- 1 Introduction to Observational Methods
- 2 Coding Schemes and Observational Measurement
- 3 Recording Observational Data
- 4 Representing Observational Data
- 5 Observer Agreement and Cohen’s Kappa
- 6 Kappas for Point-by-Point Agreement
- 7 The Intraclass Correlation Coefficient (ICC) for Summary Measures
- 8 Summary Statistics for Individual Codes
- 9 Cell and Summary Statistics for Contingency Tables
- 10 Preparing for Sequential and Other Analyses
- 11 Time-Window and Log-Linear Sequential Analysis
- 12 Recurrence Analysis and Permutation Tests
- Epilogue
- Appendix A Expected Values for Kappa Comparing Two Observers
- Appendix B Expected Values for Kappa Comparing with a Gold Standard
- References
- Index
Summary
The phrase, sequential analysis – which appears in the title of this book as well as earlier ones (Bakeman & Gottman, 1997; Bakeman & Quera, 1995a) – admits to more than one meaning. In the context of microbiology, it can refer to the description of genetic material. In the context of statistics, it can mean sequential hypothesis testing – that is, evaluating data as they are collected and terminating the study in accordance with a predefined stopping rule once significant results are obtained (Siegmund, 1985).
However, in the context of observational methods generally, and in the context of this book specifically, sequential analysis refers to attempts to detect patterns and temporal associations among behaviors within observational sessions. As such, sequential analysis is more a toolbox of techniques than one particular technique. It can include any of a variety of techniques that serve its goals. Some of these techniques have already been discussed (e.g., “Contingency indices for 2×2 tables” in Chapter 9). The unifying factor is the data used; by definition, sequential analysis is based on sequential data – data for which some sort of continuity between data points can be assumed. Indeed, a common thread throughout this book has been the description and use of the four basic sequential data types we defined in Chapter 4 – single-code event, timed-event, interval, and multicode event sequential data.
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- Publisher: Cambridge University PressPrint publication year: 2011