Sequential analysis: a guide for behavioural researchers
Gespeichert in:
Beteiligte Personen: | , |
---|---|
Format: | Buch |
Sprache: | Nichtbestimmte Sprache |
Veröffentlicht: |
Cambridge u.a.
Cambridge Univ. Pr.
2004
|
Ausgabe: | transferred to digital printing |
Schlagwörter: | |
Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015414724&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
Umfang: | IX, 275 S. |
ISBN: | 0521346657 |
Internformat
MARC
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245 | 1 | 0 | |a Sequential analysis |b a guide for behavioural researchers |c John Mordechai Gottman ; Anup Kumar Roy |
250 | |a transferred to digital printing | ||
264 | 1 | |a Cambridge u.a. |b Cambridge Univ. Pr. |c 2004 | |
300 | |a IX, 275 S. | ||
336 | |b txt |2 rdacontent | ||
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Datensatz im Suchindex
DE-BY-TUM_call_number | 0002 MAT 620f 2003 A 12586 |
---|---|
DE-BY-TUM_katkey | 1578064 |
DE-BY-TUM_location | 00 |
DE-BY-TUM_media_number | 040040318685 |
_version_ | 1821934232967053312 |
adam_text | Contents
Preface
xi
Reading this book quickly
xii
Part I: Introduction
Chapter
1:
Advertisement
3
Chapter
2:
History
9
Chapter
3:
The language of sequential analysis IS
3.1
The moving
tíme
window
16
3.2
Summary statistics
16
3.3
The base rate problem
17
3.4
The language of Markov chains
18
3.5 Markov models
19
3.6
Example
20
3.7
Higher-order Markov models
21
3.8
The odds ratio
24
3.9
Four indices of sequential connection
25
3.10
How children become friends
30
3.11
Discrete time semi-Markov models
30
3.12
Our overall plan
31
Part II: Fitting the timetable
Chapter
4:
The order of the Markov chain
35
4.1
Shannon s approximations to English
35
4.2
Information
37
4.3
The plan of our discussion
37
4.4
Likelihood ratio chi-squared tests
38
4.5
Digram structure
40
vi
Contents
4.6
Contingency-style tables
40
4.7
Independence
42
4.8
Testing independence
43
4.9
Cell wise examination of contingency tables
44
4.10
Information theory
46
4.11
Reduction in uncertainty
49
4.12
Exercise
52
4.13
Use of the LRX2 to determine order
S3
4.14
Order for specific sequences
57
Appendix
4.1:
Degrees of freedom for order of the Markov chain
58
Appendix
4.2:
LRX2
58
Chapter
5:
Stationarity of the Markov chain
60
5.1
One dyad
61
5.2
Omnibus lest for stationarity
62
5.3
Other reasons for dividing the data into segments
63
5.4
An alternative to the omnibus test
66
Chapter
6:
Homogeneity
67
6.1
Hirokawa
(1980) 68
6.2
Sillars
(1980) 68
6.3
Capella
(1980) 72
6.4
Valentine and Fisher
(1974) 72
6.5
Cline
(1979) 73
6.6
Hawes and Fofey
(1973) 75
6.7
Lichtenberg
and Hummel
(1976) 76
6.8
Hawes and Foley
(1976) 76
Chapter
7:
Everyday computations of stationarity, order and homogeneity
77
7.1
The
Annidale
programs
77
7.2
Example
77
7.3
Stationarity
78
7.4
Order
80
7.5
Homogeneity
80
7.6
Homogeneity analyses as an opportunity for discovery
80
7.7
Setting alpha levels
83
Chapters: Sampling distributions
85
8.1
Binomial distribution
85
8.2
Poisson
distribution
87
8.3
Negative binomial
88
8.4
Hypergeometric distribution
89
Contents
vii
8.5
Multinomial distribution
90
8.6
Product multinomial distribution
90
8.7
Example
92
Chapter
9:
Lag sequential analysis
95
9.1
Deciding between z-scores: The type I error rate
99
9.2
Uses of lag sequential analysis
100
9.3
A new lag sequential analysis rule of thumb
100
9.4
Detecting cyclicity
103
9.5
Studying coalitions within groups
103
9.6
Examples
103
9.6.1
Tmg-Toomey(I983)
103
9.6.2
Bakeman and Adamson
(1983) 105
9.6.3
Margolin and Wampold
(1981) 106
9.6.4
Cousins and Vincent
(1983) 108
9.6.5 Revenstorfetal.(1981)
109
9.7
Independence assumption in computing z-scores
109
Partiu:
The timetable and the contextual design
Chapter
10:
Log-linear models
113
10.1
Notation for log-linear models
1
IS
10.2
Three-way classification
117
103
Playing with the notation
118
103.1
Case(l)
118
10.3.2
Case
(2) 118
10.4
Hierarchical, non-hierarchical, and conditional nested modeb
121
10.5
Statistical tests
122
10.6
Getting expected counts
123
10.7
Model beading and »sting
126
10.8
Computing degrees of feedom
127
10.9
Model fitting step by step
127
10.10
Selecting a model by screening
129
10.11
Contrasts
130
10.12
The analysis of residuals
131
10.13
The homogeneity problem again
131
Chapter
11:
Log-linear models: review and examples
133
11.1
Model building and selection of categorical data models
133
11.2
Brown s measures of marginal and partial association
136
113
Standardized parameter
estáñales
137
11.4
Stepwise selection procedures
137
viii Contents
11.5
Examples
139
11.5.1
Brent and Sykes
(1973) 139
11.5.2
Vuchinkh
(1984) 143
11.6
Nested hierarchical models
149
11.7
Worked example
150
11.7.1
Markov model omnibus test
150
11.7.2
Log-linear analyses
151
Appendix
11.1:
Likelihood ratio tests
156
Appendix
11.2
Matrix formulation
159
Appendix
11.3:
The relationship between information theory
and log-linear models (James
T. Ringland)
161
Appendix
11.4:
Rationale for comparing models
164
Chapter
12:
A single case analysis of the timetable
168
12.1
A six-step procedure
168
12.2
Forming the timetable
170
12.3
Writing the models down
172
12.4
Preliminary consideration in comparing the models
173
12.5
Comparing models
174
12.5.1
Step
1:
Markov model analysis
174
12.5.2
Step
2:
Submodel fitting
176
12.5.3
Step
3:
Residual examination and cell removal
176
12.5.4
Step
4:
Check all reasonable submodels
177
12.5.5
Step
5:
Check larger models
178
12.5.6
Step
6:
Interpretation of the model
179
Appendix
12.1:
Freeman-Tukey deviates
187
Chapter
13:
Logit models and logistic regression
189
13.1
Introduction
189
13.2
Why we need the logit transformation
191
13.2.1
The difficulties of the standard regression model:
Linear probability model
191
13.2.2
Transformation approaches
193
13.2.3
Probit
transformation
194
132.4
Logit transformation
196
13.3
Logit analysis: grouping data across subjects within each cell
201
13.4
Logit analysis within grouping subjects: logistic regression
212
13.5
Poiytomous variables: multiple choice models
217
13.6
Incomplete tables problem of empty cells
220
13.7
Example
220
Contents ix
Appendix 13.1:
The relationship between log-linear
and logit models
222
Appendix
13.2:
Computer programs for data analysis
226
Chapter
14:
The problem of autocontingency and its solutions
228
14.1
The problem
228
14.2
Sacketťs
computational solution
230
14.3
The logit linear solution
232
143.1
Chi-squared test
232
143.2
Logit linear model
233
14.4
The Gardner-Hartmann correction
234
14.5
Untested suggestions
235
14.5.1
Binary time-series analysis solution
235
14.5.2
Controlling for autocontingency of more than
one time lag
236
Appendix
14.1:
Sacketťs
computational correction
239
Chapter
15:
Recent advances: a brief overview
240
15.1
Introduction
240
15.2
Kraemer and Jacklin
(1979);
Mendoza
and
Graziano
(1982);
and Iacobucci and
Wasserman
(1987) 241
153
Wampold and Margolin
(1982)
and Wampokt
(1984) 242
15.4
Dillon, Madden, and Kumar
(1983) 243
15 5
Feick and Novak
(1985) 243
15.6
Faraone
and Dorfman
(1987) 244
15.7
Budescu
(1984) 244
15.8
Log-linear or logit-Unear models?
245
Chapter
16: Abrief
summary
248
16.1
The data
248
16.2
Forming the timetable: determining order and stationarity
248
163
Homogeneity: the decisions of how to best group subjects
248
16.4
Within-subject analyses
249
163
Pooling across subjects
249
16.6
Doing the minimum
249
References
251
Index
265
|
any_adam_object | 1 |
author | Gottman, John Mordechai 1942- Roy, Anup K. |
author_GND | (DE-588)120462435 |
author_facet | Gottman, John Mordechai 1942- Roy, Anup K. |
author_role | aut aut |
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author_variant | j m g jm jmg a k r ak akr |
building | Verbundindex |
bvnumber | BV022203298 |
classification_rvk | CV 2000 |
classification_tum | MAT 632f PSY 470f |
ctrlnum | (OCoLC)634634107 (DE-599)BVBBV022203298 |
discipline | Psychologie Mathematik |
edition | transferred to digital printing |
format | Book |
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genre_facet | Konferenzschrift |
id | DE-604.BV022203298 |
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indexdate | 2024-12-20T12:49:59Z |
institution | BVB |
isbn | 0521346657 |
language | Undetermined |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015414724 |
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physical | IX, 275 S. |
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publisher | Cambridge Univ. Pr. |
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spellingShingle | Gottman, John Mordechai 1942- Roy, Anup K. Sequential analysis a guide for behavioural researchers Sozialwissenschaften (DE-588)4055916-6 gnd Interaktion (DE-588)4027266-7 gnd Verhaltenswissenschaften (DE-588)4133253-2 gnd Sequentialanalyse (DE-588)4128461-6 gnd |
subject_GND | (DE-588)4055916-6 (DE-588)4027266-7 (DE-588)4133253-2 (DE-588)4128461-6 (DE-588)1071861417 |
title | Sequential analysis a guide for behavioural researchers |
title_auth | Sequential analysis a guide for behavioural researchers |
title_exact_search | Sequential analysis a guide for behavioural researchers |
title_full | Sequential analysis a guide for behavioural researchers John Mordechai Gottman ; Anup Kumar Roy |
title_fullStr | Sequential analysis a guide for behavioural researchers John Mordechai Gottman ; Anup Kumar Roy |
title_full_unstemmed | Sequential analysis a guide for behavioural researchers John Mordechai Gottman ; Anup Kumar Roy |
title_short | Sequential analysis |
title_sort | sequential analysis a guide for behavioural researchers |
title_sub | a guide for behavioural researchers |
topic | Sozialwissenschaften (DE-588)4055916-6 gnd Interaktion (DE-588)4027266-7 gnd Verhaltenswissenschaften (DE-588)4133253-2 gnd Sequentialanalyse (DE-588)4128461-6 gnd |
topic_facet | Sozialwissenschaften Interaktion Verhaltenswissenschaften Sequentialanalyse Konferenzschrift |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015414724&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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