Sequential Analysis: A Guide for Behavioral ResearchersSequential Analysis aims to detect the recurring sequential patterns in a stream of coding categories describing social interaction. These techniques can be employed to study the repertoires of individuals and of dyads and groups. This book is a sequel to Bakeman and Gottman's Observing Interaction: An Introduction to Sequential Analysis (CUP, 1986). It constitutes the first integrated presentation of the major methods of sequential analysis. Gottman and Roy review historical approaches such as stationarity, order, homogeneity, pooling data across subjects, and autocorrelation in inferring cross-correlation. The integrated application of techniques is also discussed. Addressing the behavioral scientist, the authors provide many examples and illustrate everyday computations. They also offer guides to existing computer programs. |
Contents
Lag sequential analysis | 9 |
The order of the Markov chain | 35 |
Degrees of freedom for order of the Markov chain | 58 |
Homogeneity | 67 |
Everyday computations of stationarity order and homogeneity | 77 |
Sampling distributions | 85 |
Loglinear models | 113 |
85 | 126 |
87 | 152 |
Likelihood ratio tests | 156 |
Rationale for comparing models | 164 |
FreemanTukey deviates | 187 |
The problem of autocontingency and its solutions | 228 |
Sacketts computational correction | 239 |
A brief summary | 248 |
Index | 265 |
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Sequential Analysis: A Guide for Behavioral Researchers John Mordechai Gottman,Anup Kumar Roy No preview available - 2008 |
Common terms and phrases
1st-Order 2nd-Order analysis of variance antecedent asymptotically Bakeman behavior binomial cell chi-squared test coding system compared compute conditional probability conflict contextual design contingency table couples degrees of freedom denote dependent digram structure discussion distribution dyad Effective group Equation estimate event example expected counts factors first-order Markov function Gottman hierarchical models homogeneity husband independent variables infant interaction term iteration lag sequential likelihood ratio log-linear models log2 logit model LRX2 main effects marginal marital interaction Markov chain Markov model methods moving time window negative affect nondistressed notation null hypothesis number of observations occur omnibus tests pairs parameters Poisson predicted problem procedure reciprocity regression Sackett sample saturated model segments sequence sequential analysis sequential connection significant social speaker square stationarity statistic techniques three-way timetable tion tive transition frequency transition matrix transition probabilities trigram unconditional values Wampold z-scores zero
Popular passages
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Page 262 - PLACKETT, RL 1974 The Analysis of Categorical Data. London: Griffin. PLACKETT, RL, AND PAUL, SR 1978 "Dirichlet models for square contingency tables." Communications in Statistics: Theory and Methods A7(10):939-952. STUART, A. 1953 "The estimation and comparison of strengths of association in contingency tables.