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Lindsey J.K. — Applying generalized linear models
Lindsey J.K. — Applying generalized linear models

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Название: Applying generalized linear models

Автор: Lindsey J.K.

Аннотация:

Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview whereby they can see that the three areas - linear normal, categorical, and survival models - have much in common. The author shows the unity of many of the commonly used models and provides the reader with a taste of many different areas, such as survival models, time series, and spatial analysis. This book should appeal to applied statisticians and to scientists with a basic grounding in modern statistics. With the many exercises included at the ends of chapters, it will be an excellent text for teaching the fundamental uses of statistical modelling. The reader is assumed to have knowledge of basic statistical principles, whether from a Bayesian, frequentist, or direct likelihood point of view, and should be familiar at least with the analysis of the simpler normal linear models, regression and ANOVA. The author is professor in the biostatistics department at Limburgs University, Diepenbeek, in the social science department at the University of Liège, and in medical statistics at DeMontfort University, Leicester. He is the author of nine other books.


Язык: en

Рубрика: Математика/Вероятность/Статистика и приложения/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 1997

Количество страниц: 257

Добавлена в каталог: 05.06.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Aalen      127 136
Absorbing event      109 121 122 124
Accelerated lifetime model      122
Ackerson      176
Agresti      44
AIC      3 24 209
Aitkin      vii 25 113
Akaike      3 209
Akaike information criterion      3 24 209
Alias      16 202
Alias, extrinsic      16 26 202
Alias, intrinsic      16 26
Altham      208
Altman      1 2
Analysis of covariance      161
Analysis of deviance      214
Analysis of variance      4 29 161
Andersen, A.H.      190
Andersen, E.B.      41 66
Andersen, P.K.      117 126 136
Andrews      94 106
Angelis, de      85
anova      vii 4 7 30 161 215
Anscombe      104
Approximate likelihood function      198
Armitage      5
Asymptote      69 74 75 84 181—184 194 195
Autocorrelation      93 94 175 176 181 182 184
Autoregression model      93 94 97 98 102 103 159 173—178
Barndorff-Nielsen      25
Barnett      229
Barnhart      67
Baseline constraint      17
Baseline hazard function      114 116
Baskerville      128—130 132
Bates      167
Bayes' formula      174 193 216 217
Bayesian decision-making      215
Bayesian information criterion      209
Bennett      84
Berger      219
Berkson      5
Bernoulli distribution      5 211 222 227
Besag      142
Beta distribution      39 186
Beta-binomial distribution      39 186
Beta-negative binomial distribution      187 193 194
Beveridge      98 99 105
BIC      209
Binomial distribution      4 10 13 19 20 25 27 28 30 37—39 53 58 59 65 112 124 125 127 198 199 203 204 210
Binomial distribution, double      58 59
Binomial distribution, multiplicative      58 59
Binomial process      186
Birch      5
Birth process      37 90 145
Birth process, Weibull      90
Bishop      44
BLISS      4
Blossfeld      136
Boadi — Boateng      177
box      162—165 167 219
Brown, B.M.      170
Brown, L.D.      25
Burridge      55
Buxton      170
Calibrated deviance      209
Canonical form      10 11 49 216
Canonical linear predictor      71
Canonical link      19 21 42 96 159 164 166 199
Canonical parameter      13 19 52 53
Canonical statistic      217
Carryover effect      128 129 131 132
Case-control study      30
Censoring      8 23 66 109 111 112 114 118 119 124 139 140 199
Chi-squared distribution      25 212
Clayton      113
Clinical trial      122 128 129 178
Closure under sampling      216
Cochran      168
Coleman      45
Collett      44
Compatible inference      207 208
Complementary log log link      4 21 42 75 145 199
Complete model      14
Composite link      23
Compound distribution      38 39 216—218
Conditional distribution      31 50 93 141 143 159 175 177 178
Conditional mean      93
Conditional probability      28 33
Confidence interval      25 212
Confirmatory inference      24
Conjugate distribution      38 39 186 189 196 216—219
Constraint      17 29—31
Constraint, baseline      17
Constraint, conventional      17 202
Constraint, usual      17
Contagion process      37 90
Continuous time      87 116 125 127 176—178 191
Control      57 180
Conventional constraint      17 202
Cook      228 229
Cook's distance      42 228
Correlation      159
Correlation, intraclass      180 182
Correlation, serial      177 178
Counts      5 8 27 38 57 88 94 146 154 156 164 186 194
Counts, micronuclei      60
Counts, zero      60
Covariance      182 184 218
Covariance analysis      161
Covariance matrix      159 177 178
Cox      117 162—164 167 219
Cressie      150 151 154
Crossover experiment      128—130 169
Crouchley      92
Crowder      103
Data generating mechanism      6
Data, abortion      46
Data, AIDS, UK      85
Data, AIDS, USA      73
Data, ant nests      154
Data, baboons      126
Data, barley      155
Data, bedload      134 135
Data, capital formation      71
Data, car occupants      65
Data, coal ash      157
Data, Danish wealth      66
Data, Danish welfare      41
Data, divorces      67
Data, dog learning      137
Data, exercises      84
Data, eyes      45
Data, flies mating      136
Data, gallstones      139
Data, Geiger counter      64
Data, goldfish      161
Data, growth, beans      82
Data, growth, pika      82
Data, growth, sunflowers      82
Data, half-emptying time      169
Data, horse kicks      106
Data, iron ore      158
Data, lambs      63
Data, leading crowd      45
Data, lynx      94
Data, micronucleus      61
Data, microwave tower      152
Data, migration, Britain      33
Data, migration, Wisconsin      92
Data, mine disasters      66
Data, neighbours, trees      148
Data, neighbours, vegetation      156
Data, nuclear waste      151
Data, Paramecium      194
Data, plants      143
Data, Post Offce employment      55
Data, postal survey      57
Data, preference trial      130
Data, rainfall      138
Data, rat weights      168
Data, sex of children      59 65
Data, sheep      168
Data, snowfall      104
Data, social mobility      44
Data, stressful events      50
Data, suicides      89
Data, sunspots      103
Data, survival, animal      168
Data, survival, black ducks      119
Data, survival, gastric cancer      118
Data, survival, leukemia      112 117
Data, survival, lymphoma      118
Data, timber      170
Data, viscometer      166
Data, vote, Britain      44
Data, vote, Sweden      35
Data, welds      170
Data, Winchester wages      99 105
Data, women working      105
Data, wool      163
Data, Yale enrollment      104
Davison      229
Decarli      25
Decision-making Bayesian      215
Decision-making frequentist      212
Degrees of freedom      206
Departure, isolated      226
Departure, minimal      228
Departure, systematic      222
Derman      65
Design matrix      14 16 18
Deviance      204 227
Deviance residual      98 223 224
Deviance statistic      212
Deviance, calibrated      209
Diagnostics      221 222
Diggle      103 188 194
Dinse      118
Discrete time      87 101 123–125 127 128 141 176—178
Dispersion parameter      13 15 22 223
Distribution, Bernoulli      5 211 222 227
Distribution, Beta      39 186
Distribution, beta-binomial      39 186
Distribution, beta-negative binomial      187 193 194
Distribution, binomial      4 10 13 19 20 25 27 28 30 37—39 53 58 59 65 112 124 125 127 198 199 203 204 210
Distribution, binomial, double      58 59
Distribution, binomialmultiplicative      58 59
Distribution, chi-squared      25 212
Distribution, compound      38 39 216—218
Distribution, conditional      31 50 93 141 143 159 175 177 178
Distribution, conjugate      38 39 186 189 196 216—219
Distribution, exponential      5 20 21 23 25 51 53 113 114 116 117 122 124 125 199
Distribution, exponential, piecewise      116 125
Distribution, extreme value      23 122
Distribution, gamma      3 5 11 13 19—21 39 53 55 56 70 71 96—98 100 109 122 161 162 164—166 186 189 191 193 199 210 217 219
Distribution, geometric      53 128
Distribution, hypergeometric      186 187
Distribution, inverse Gaussian      3 13 19 21 53 96 98 100 109 122 164 189
Distribution, log gamma      20 70
Distribution, log logistic      122
Distribution, log normal      3 20 53 55 70 71 94—97 109 122 161 162 164 165 189
Distribution, logistic      23
Distribution, marginal      93 186 216—218
Distribution, mixture      60 62 64
Distribution, multinomial      27 29—31 49 50 54 208
Distribution, multivariate      6 63 64 87 141—144 174 177
Distribution, negative binomial      3 4 22 39 97 98 164 187 195
Distribution, normal      v vii 1—3 5 7 9 11 13 18—20 25 27 28 38 39 44 53 70 71 93 98 101 109 150 159 162 164–167 173 175—177 195 199 205 210 214 218 219 222—225
Distribution, normal, multivariate      159
Distribution, normal, standard      226
Distribution, Pareto      20 53
Distribution, Poisson      2 3 5 10 13 19 20 23 26 27 29 30 37—39 49 50 52 53 55 60 71 88 97 113 114 123 125 127 142 145 186 210 217 219
Distribution, Poisson, bivariate      63
Distribution, Poisson, truncated      57
Distribution, posterior      191 193 215—217 219
Distribution, prior      191 193 215—218
Distribution, prior, conjugate      216—219
Distribution, prior, flat      219
Distribution, prior, improper      219
Distribution, prior, Jeffreys'      219
Distribution, prior, noninformative      219
Distribution, prior, truncated      57 60 64
Distribution, uniform      53
Distribution, Weibull      21 23 25 78 113—117 122 124 125
Dobson, vii      25
Double blinded experiment      128 178
Drift      35
Duration      vii 7 8 55 102 109 121 122 128 170 189
Dyke      5
Dynamic generalized linear model      173 174 186 189 190 192 195
Dynamic linear model      175–177
Educational testing      39
Edwards      219
Embedded model      223
Endogenous variable      184
Error estimation      177
Error recording      226
Error sampling      226
Error standard      202 224
Error structure      18 70
Estimate interval      202
Estimate Kaplan — Meier      111 112 125
Estimate maximum likelihood      5 21 51 112 116 124 199 200 205 215 225
Estimate Nelson — Aalen      125
Estimate product limit      111 112
Event history      88 102 109 113 121—124 127 128 136 139
Expected information      201 212
Expected residual      93
Experiment      4 26 64 166 171 193 204 207 210
Experiment kinesiology      84
Experiment, crossover      128—130 169
Experiment, double blinded      128 178
Experiment, factorial      162 168
Experiment, response surface      160 161
Experiment, Solomon — Wynne      137
Explanatory variable      8
Explanatory variable, time-varying      87 88 113 121 122 125 183
Exploratory inference      24 221
Exponent link      21 22
Exponential dispersion family      1 5 6 9 11 12 18—22 25 38 159 200 210 214 217 218 223
Exponential distribution      5 20 21 23 25 51 53 113 114 116 117 122 124 125 199
Exponential family      4 5 10 11 22 25 27 37 38 52—54 57 58 64 70 96 142 199 204 216 217 219
Exponential growth curve      51 70 72 74 76 78 96 181
Extreme value distribution      23 122
Extreme value process      88
Extrinsic alias      16 26 202
Factor variable      14 16 24 29 33 34 36 40 60 77—79 90 91 102 113 116 125 129 146 161 162 164 215
Factorial experiment      162 168
Factorial model      16 162
Fahrmeir      vii 25 103 196
Family, exponential      4 5 10 11 22 25 27 37 38 52—54 57 58 64 70 96 142 199 204 216 217 219
Family, exponential dispersion      1 5 6 9 11 12 18—22 25 38 159 200 210 214 217 218 223
Feigl      5 117
Feller      155
Fernandes      196
Fingleton      33 154
Fisher      4 5 65
Fisher information      26 201
Fitted value      77 79 80 189 200 222 224 227
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