Nonparametric Tests for Censored Data

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Edition: 1st
Format: Hardcover
Pub. Date: 2011-01-18
Publisher(s): Wiley-ISTE
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Summary

This book concerns testing hypotheses in non-parametric models. Generalizations of many non-parametric tests to the case of censored and truncated data are considered. Most of the test results are proved and real applications are illustrated using examples. Theories and exercises are provided. The incorrect use of many tests applying most statistical software is highlighted and discussed.

Author Biography

Vilijandas Bagdonavicius is Professor of Mathematics at the University of Vilnius in Lithuania. His main research areas are statistics, reliability and survival analysis. Julius Kruopis is Associate Professor of Mathematics at the University of Vilnius in Lithuania. His main research areas are statistics and quality control.

Table of Contents

Prefacep. xi
Terms and Notationp. xv
Censored and Truncated Datap. 1
Right-censored datap. 2
Left truncationp. 12
Left truncation and right censoringp. 14
Nelson-Aalen and Kaplan-Meier estimatorsp. 15
Bibliographic notesp. 17
Chi-squared Testsp. 19
Chi-squared test for composite hypothesisp. 19
Chi-squared test for exponential distributionsp. 31
Chi-squared tests for shape-scale distribution familiesp. 36
Chi-squared test for the Weibull distributionp. 39
Chi-squared tests for the loglogistic distributionp. 44
Chi-squared test for the lognormal distributionp. 46
Chi-squared tests for other familiesp. 51
Chi-squared test for the Gompertz distributionp. 53
Chi-squared test for distribution with hyperbolic hazard functionp. 56
Bibliographic notesp. 59
Exercisesp. 59
Answersp. 60
Homogeneity Tests for Independent Populationsp. 63
Datap. 64
Weighted logrank statisticsp. 64
Logrank test statistics as weighted sums of differences between observed and expected number of failuresp. 66
Examples of weightsp. 67
Weighted logrank statistics as modified score statisticsp. 69
The first two moments of weighted logrank statisticsp. 71
Asymptotic properties of weighted logrank statisticsp. 73
Weighted logrank testsp. 80
Homogeneity testing when alternatives are crossings of survival functionsp. 85
Alternativesp. 86
Modified score statisticsp. 88
Limit distribution of the modified score statisticsp. 91
Homogeneity tests against crossing survival functions alternativesp. 92
Bibliographic notesp. 97
Exercisesp. 98
Answersp. 102
Homogeneity Tests for Related Populationsp. 105
Paired samplesp. 106
Datap. 106
Test statisticsp. 107
Asymptotic distribution of the test statisticp. 107
The testp. 116
Logrank-type tests for homogeneity of related k > 2 samplesp. 119
Homogeneity tests for related samples against crossing marginal survival functions alternativesp. 122
Bibliographic notesp. 124
Exercisesp. 125
Answersp. 126
Goodness-of-fit for Regression Modelsp. 127
Goodness-of-fit for the semi-parametric Cox modelp. 127
The Cox modelp. 127
Alternatives to the Cox model based on expanded modelsp. 128
The data and the modified score statisticsp. 129
Asymptotic distribution of the modified score statisticp. 133
Testsp. 137
Chi-squared goodness-of-fit tests for parametric AFT modelsp. 142
Accelerated failure time modelp. 142
Parametric AFT modelp. 144
Datap. 144
Idea of test constructionp. 145
Asymptotic distribution of Hn and Zp. 146
Test statisticsp. 151
Chi-squared test for the exponential AFT modelp. 153
Chi-squared tests for scale-shape APT modelsp. 159
Chi-squared test for the Weibull AFT modelp. 163
Chi-squared test for the lognormal AFT modelp. 166
Chi-squared test for the loglogistic AFT modelp. 169
Bibliographic notesp. 172
Exercisesp. 173
Answersp. 174
Appendicesp. 177
Maximum Likelihood Method for Censored Samplesp. 179
ML estimators: right censoringp. 179
ML estimators: left truncationp. 181
ML estimators: left truncation and right censoringp. 182
Consistency and asymptotic normality of the ML estimatorsp. 186
Parametric ML estimation for survival regression modelsp. 187
Notions from the Theory of Stochastic Processesp. 191
Stochastic processp. 191
Counting processp. 193
Martingale and local martingalep. 194
Stochastic integralp. 195
Predictable process and Doob-Meyer decompositionp. 197
Predictable variation and predictable covariationp. 198
Stochastic integrals with respect to martingalesp. 204
Central limit theorem for martingalesp. 207
Semi-parametric Estimation using the Cox Modelp. 211
Partial likelihoodp. 211
Asymptotic properties of estimatorsp. 213
Bibliographyp. 225
Indexp. 231
Table of Contents provided by Ingram. All Rights Reserved.

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