√лавна€    Ex Libris     ниги    ∆урналы    —татьи    —ерии     аталог    Wanted    «агрузка    ’удЋит    —правка    ѕоиск по индексам    ѕоиск    ‘орум   
blank
јвторизаци€

       
blank
ѕоиск по указател€м

blank
blank
blank
 расота
blank
Little R.J.A., Rubin D.B. Ч Statistical analysis with missing data
Little R.J.A., Rubin D.B. Ч Statistical analysis with missing data

„итать книгу
бесплатно

—качать книгу с нашего сайта нельз€

ќбсудите книгу на научном форуме



Ќашли опечатку?
¬ыделите ее мышкой и нажмите Ctrl+Enter


Ќазвание: Statistical analysis with missing data

јвторы: Little R.J.A., Rubin D.B.

јннотаци€:

Statistical analysis of data sets with missing values is a pervasive problem for which standard methods are of limited value. "Statistical Analysis with Missing Data" is a standard reference on missing-data methods.
Blending theory and application, authors Roderick Little and Donald Rubin review historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values. They then provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing-data mechanism and apply the theory to a wide range of important missing-data problems.


язык: en

–убрика: Computer science/

—татус предметного указател€: √отов указатель с номерами страниц

ed2k: ed2k stats

√од издани€: 1987

 оличество страниц: 278

ƒобавлена в каталог: 08.12.2005

ќперации: ѕоложить на полку | —копировать ссылку дл€ форума | —копировать ID
blank
ѕредметный указатель
Acceleration techniques      27
Additive model      253
Adjusting standard errors for filled-in missing values      32Ч34
Adjusting sums of squares for filled-in missing values      34Ч36
Adjustment cell      56Ч57 254
Adjustment cell, models      250Ч253 260Ч261
Afifi, A. A.      6 18 39 48
Aitkin, M.      208 216
Algorithms, iterative      128Ч129 (see also EM algorithm Newton-Raphson Scoring
Allan, F. G.      26 36 37
allocation      (see Filling in for missing values)
ALLVALUE estimates      42
Amemiya, T.      223 224 241
Analysis of covariance (Ancova)      27Ч30
Analysis of variance (Anova)      14 21Ч38 94 152Ч153 203Ч206
Analysis of variance (ANOVA), mixed effects      149Ч152
Analysis of variance (ANOVA), random effects      149Ч152
Anderson, R. L.      22 36
Anderson, T. W.      82 95 98 119 120 124 125 204 216
Approximate Bayesian bootstrap      258Ч259
Approximate covariance matrix      98 154
AR1 Model      163
Association, in contingency tables      185
Asymptotic approximations, accuracy      105Ч107
Asymptotic covariance matrix of parameters or estimates      84Ч86
Asymptotic covariance matrix of parameters or estimates for categorical data      180
Asymptotic covariance matrix of parameters or estimates for general missing data pattern      137 139
Asymptotic covariance matrix of parameters or estimates for multiple regression      154
Asymptotic covariance matrix of parameters or estimates for multivariate normal data      145
Asymptotic normality      84Ч86
Asymptotic standard errors      (see Asymptotic covariance matrix of parameters or estimates)
Augmented covariance matrix, definition      114
Autoregressive model      158 161 165
Autoregressive model, moving average (ARMA) models      162
Available-case methods      41 43 49 109Ч112 169
Azen, S.      43 48 49
Baghelai, C.      169
Bailar, B. A.      65 71
Bailar, J. C.      65 71
Bailey, L.      65 71
Baker, S.      237 240 241
Balanced repeated replication      71
Banded covariance structure      158 161
Bard, Y.      93 95
Bargmann, R. W.      145 169
Bartlett, M. S.      27 29 36 37
BartlettТs method      27Ч30
Baum, L. E.      129 139
Bayesian bootstrap      265
Bayesian inference      53 84Ч88 93 104Ч107 230Ч235 244Ч265
Beale, E. M. L.      129 139 144 145 154 155 168 170
Beaton, A. E.      112 124
Bemdt, E. B.      128 139 224 241
Bent, D. H.      19
Bentler, P. M.      168 170
Beta distribution      95
Between-imputation variance      257
Bias due to nonresponse      15Ч17 53 Nonignorable
Bias vs. variance      70
Binomial distribution      140
Bishop, Y. M. M.      172 173 186 187 193
Bivariate data      13Ч16 49
Bivariate data, normal data      14 83 92 96 125Ч126 169Ч170
Bivariate data, normal data, EM algorithm      132Ч134
Bivariate data, normal data, ML estimation      98Ч102
Bivariate data, normal data, precision of estimation      102Ч107
Bivariate data, normal monotone data      98Ч107 115
Bivariate data, normal stochastic censoring model      224
Bivariate data, time series      167
BMDP statistical software, 4F      189
BMDP statistical software, 8D      41 42 126
BMDP statistical software, AM      4
Bobula, J.      169
Bootstrap      71 265
Box Ч Cox power transformation      228Ч229
Box Ч Jenkins models      162
Box, G. E. P.      87 95 104 124 125 162 168 227 241 264 265
Box, M. J.      93 95
Brown, D. T.      204 216
Brownlee, K. A.      152 168
Buck, S. F.      44 45 46 47 48 49
BuckТs method      45 47 49
Caines, P. E.      165 168
Calibration experiment      14
Candidates for imputation      66
Canonical correlation      142
Cassell, C. M.      58 71 73
categorical data      4Ч5 95 131Ч132 171-194 196Ч217 261
Categorical data, independence model      182 253
Categorical data, nonignorable models      235Ч241 (see also Loglinear models)
Cauchy distribution      95
Censored data      9Ч13 91Ч92 141 219 221Ч230
Censored data with known censoring points      10 94Ч95 141 222Ч223
Censored data with stochastic censoring points      10Ч12 223 224Ч225 230
Censored data, exponential sample      94Ч95 141 222
Central limit theorem      52 85
Chen, T.      183 193
Chi-squared statistics      (see Likelihood ratio statistic Goodness-of-fit
Circular symmetry pattern      147
Clarke, W. R.      4 5 19
Cluster analysis with missing data      (see Mixture models)
Cluster samples      69
Cochran, W. G.      21 31 32 36 37 51 53 63 66 71 101 124 125 150 169 247 254 264
Cold deck imputation      60
Colledge, M. J.      66 71
Comparison of missing-data methods      109Ч112 228 262Ч264
Compensatory reading example      234Ч235
Complete-case methods      40 41 49 110Ч112
Complete-data likelihood      130 134
Complete-data sufficient statistics      138
Compound symmetry      158
Computational strategies      127Ч141
Computer packages, missing-data methods in      3Ч4 6
Conditional independence      148 239
Confirmatory factor analysis      149
Consistent estimates from incomplete data      (see Inference based on maximum likelihood theory Missing
Contaminated normal model      209Ч216
Contaminated normal model, multivariate normal model      211Ч216
Contingency table      (see Categorical data Loglinear
Contrasts      32Ч36
Convergence, quadratic      140
Corby, C.      65 71
Correlations, estimates from incomplete data      40Ч41 42 43 46 105Ч107
Correlations, inestimable      120Ч124
Cosier, J.      169
Counted data      (see Categorical data)
Covariance components models      150
Covariance matrix of estimates      84Ч85
Covariance matrix, estimation from incomplete data      39Ч41 142Ч145
Covariance matrix, robust estimation      211Ч215 (see also Asymptotic covariance matrix of parameters or estimates)
Cox, D. R.      79 84 95 227 241
Cox, G.      21 31 32 36
Current Population Survey      65 227
Curry, J.      43 48 49
DarwinТs data      208
Data matrix      3 19
David, M. H.      60 61 62 71 229 241
Davies, O. L.      21 36
Dawid, A. P.      54 71
Day, N. E.      207 216
Degrees of freedom for lack of fit in contingency tables      186Ч188 192 237Ч241
Degrees of freedom, corrections      23 29 32 34 35 144
DeGroot, M. H.      93 95
Deleting observed values      (see Discarding data)
Dempster, A. P.      6 18 43 48 112 124 129 130 131 135 136 137 139 145 150 152 168 209 210 216
Density function      79
Dependent variables, missing values in      21Ч38 152Ч157 196 203 220-230 232Ч235
Design weights      6
Design-based inference in surveys      (see Randomization inference for surveys)
Dichotomous data      48 (see also Categorical data)
Discarding data      6 19 109Ч112
Discrete data      (see Categorical data)
Discriminant analysis      142 196Ч206
Distinct parameters      90 97
distribution      209
Dixon, W. J.      4 19 41 42 48 124 126 189 193
Donor for imputation      63 66
Double sampling      9 254
Draper, N. R      23 36 93 95 117 124
Dummy variable regression      108 254
E step (expectation step)      130 (see also EM algorithm)
EAТs      (see Enumeration areas (EAТs))
editing      (see Outliers)
Educational testing      121Ч124
Educational testing, examples      148
Efficiency      175
Elashoff, R. M.      6 18 39 48
EM algorithm      18 26 129Ч139 140
EM algorithm for exponential families      138Ч139
EM algorithm for nonignorable missing data      220Ч221
EM algorithm for specific missing-data problems factor analysis      148Ч149
EM algorithm for specific missing-data problems grouped exponential sample      221Ч222
EM algorithm for specific missing-data problems grouped normal data with covariates      222Ч224
EM algorithm for specific missing-data problems log-linear models      187Ч191
EM algorithm for specific missing-data problems logistic regression      196
EM algorithm for specific missing-data problems missing outcomes in ANOVA      152Ч153
EM algorithm for specific missing-data problems mixed continuous and categorical data      195Ч208
EM algorithm for specific missing-data problems multivariate non-normal data      209Ч216
EM algorithm for specific missing-data problems multivariate normal data      143Ч145
EM algorithm for specific missing-data problems multivariate regression      155Ч157 215Ч216
EM algorithm for specific missing-data problems partially classified contingency tables      181Ч185 240
EM algorithm for specific missing-data problems regression      153Ч154 196
EM algorithm for specific missing-data problems repeated measures models      158
EM algorithm for specific missing-data problems restricted covariance matrix      146Ч148 158
EM algorithm for specific missing-data problems selection models      224Ч225
EM algorithm for specific missing-data problems time series      163Ч168
EM algorithm for specific missing-data problems variance components      149Ч152 143Ч145
EM algorithm for specific missing-data problems with follow-up data      243
EM algorithm, convergence      129 130 135 137 140
EM algorithm, rate of convergence      137Ч138
EM algorithm, theory      134Ч137 138Ч139 220-221
Empirical Bayes model      149Ч152
Enumeration areas (EAТs)      68
Ernst, L. R.      60 71
Expectation-maximization algorithm      (see EM algorithm)
Expected mean squares      152
experiments      16 21Ч38 152Ч153
Exploratory factor analysis      149
Exponential data      80 82 86 90Ч92
Exponential data with censored values      94Ч95 141 222
Exponential data with grouped values      221Ч222
Exponential distribution      221Ч222
Exponential family      136 138Ч139 140 197 204
F distribution      23
Factor analysis      148Ч149 158 170
Factor analysis with missing data      149
Factor analysis, loading matrix      148
Factor analysis, score matrix      148
Factored likelihood      15 97Ч98
Factored likelihood for bivariate normal data      98Ч101
Factored likelihood for mixed continuous and categorical data      206Ч207 217
Factored likelihood for monotone data      107Ч108 215Ч216
Factored likelihood for multivariate normal data      108Ч112
Factored likelihood for partially classified contingency tables      172Ч181 239
Factored likelihood for special nonmonotone patterns      119Ч124
Factored likelihood, computations via SWEEP      115Ч119 122Ч124
Factorization table      126
Fay, R. E.      237 241
Fienberg, S. E.      172 173 183 186 187 193
File matching      121
Filling in for missing values      6 21Ч38 43 47 60Ч67 254Ч259
Filling in for missing values and iterating      26Ч27 129
Filling in for missing values and using complete data methods      30Ч37
Filling in for missing values and using formulas      26
Filling in for missing values, conditional means, as from regression      25 45 47 61 102 253Ч255
Filling in for missing values, least squares estimates      25
Filling in for missing values, relationship with weighting      62
Filling in for missing values, stochastically, to preserve distributions      47 60 61 62Ч67 254Ч259
Filling in for missing values, unconditional means      44
Finite population      50
Finite population, correction      247
Finite population, inference model-based      244Ч265
Finite population, inference randomization-based      50 75
Fisher, R. A.      26
follow-ups      243 262Ч264
Ford, B. N.      60 71
Forecasting      165
Fraction of information missing      257
Frequency data      (see Categorical data)
Frequentist inference      84Ч88
Fuchs, C.      175 178 189 192 193
Fully missing variables      146
Fully normal imputation      259 265
Galke, W.      223 241
Gamma distribution      140 210
Gaussian distribution      (see Normal data)
GEM algorithm      (see Generalized EM algorithm)
General location model      196 206 217
General missing-data patterns      17Ч18
General state space models      162
Generalized EM algorithm      135 158 204
Glynn, R.      262 264
Goel, K.      93 95
Goodman, C.      169
Goodman, L. A.      17 186
Goodness-of-fit statistics      186 192
Goodnight, J. H.      112 124
Goodrich, R. L.      165 168
Greenlees, W. S.      230 241
Grouped and rounded data      211 221 223
Grouped and rounded data, exponential sample      221Ч222
Grouped and rounded data, normal data      222 223
Growth curve models      158Ч161
Gupta, N. K.      165 168
Haberman, S. J.      186 193
Haitovsky, Y.      43 48 49
Hajek, J.      52 71
Hall, B.      139 241
Hall, R.      139 241
Hansen, M. H.      51 71 254 264
Hartley, H. O.      6 19 26 36 129 139 145 168 182 193
Harvey, A. C.      162 168
Hasselblad, V.      223 241
Hausman, J. A.      139 241
Healy, M. J. R.      26 36 153 168
Heckman, J.      224 229 230 241
HeckmanТs two-step method      229Ч230
Helms, R. W.      157 168
Herson, J.      254 264
Herzog, T. N.      61 72 255 256 258 264
Heterogeneity of variance      254
Hierarchical loglinear models      186 235
Hinkley, D. V.      79 84 95
Historical heights      12Ч13
Hocking, R. R.      6 19 145 168 177 179 193
Holland, P. W.      148 168 172 173 186 187 193
Horvitz Ч Thompson estimator      55 56 69 73
Horvitz, D. G.      55 56 69 72 73
Hot deck imputation      6 60 62Ч67 75 256 258 265
Hot deck imputation within adjustment cells      65
Hot deck imputation, increase in variance of estimation      64Ч65 75
Hot deck imputation, metric, nearest neighbor      65Ч67
Hot deck imputation, random sampling with replacement      63Ч64
Hot deck imputation, random sampling without replacement      64Ч65
Hot deck imputation, sequential      65Ч67
Hull, C. H.      19
Hunter, W. G.      93 95
Hurwitz, W. N.      51 71
Hypothesis testing      87Ч88 (see also Likelihood ratio statistic)
Ignorable missing-data mechanism      9 10Ч13 55 248 250Ч255
1 2 3
blank
–еклама
blank
blank
HR
@Mail.ru
       © Ёлектронна€ библиотека попечительского совета мехмата ћ√”, 2004-2017
Ёлектронна€ библиотека мехмата ћ√” | Valid HTML 4.01! | Valid CSS! ќ проекте