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
12 - Recurrence Analysis and Permutation Tests
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 analytic techniques presented so far have relied primarily on summary scores derived from sequential data; depending on the technique, they could be applied to one or more of the data types that we have described (i.e., single-code event, timed-event, interval, and multicode event data). In this final chapter we describe two additional techniques for detecting pattern. One is primarily graphic and can be applied to any kind of sequence; the other is a statistical approach to detecting pattern in relatively short single-code event sequences and requires few assumptions.
Recurrence Analysis
In this section we consider techniques that rely on whole sequences to display patterns graphically. Exploring a sequence as a whole can provide new insight into any patterns that may exist, where in the sequence they occur, and even whether they tend to repeat in different, but comparable, sequences. Moreover, such explorations can also be applied to two sequences to determine whether certain codes tend to repeat in both, thus revealing a possible synchronicity.
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- Publisher: Cambridge University PressPrint publication year: 2011
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