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Continuous failure times and their causes |
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1 | (18) |
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Basic probability functions |
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1 | (5) |
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Univariate survival distributions |
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1 | (3) |
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A time and a cause: Competing Risks |
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4 | (2) |
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6 | (4) |
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10 | (3) |
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Sub-hazards and overall hazard |
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10 | (2) |
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12 | (1) |
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13 | (6) |
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15 | (1) |
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16 | (1) |
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16 | (1) |
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16 | (3) |
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Parametric likelihood inference |
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19 | (18) |
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The likelihood for Competing Risks |
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19 | (3) |
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Forms of the likelihood function |
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19 | (1) |
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Incomplete observation of C or T |
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20 | (1) |
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Maximum likelihood estimates |
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21 | (1) |
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22 | (2) |
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22 | (1) |
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23 | (1) |
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24 | (3) |
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Hypothesis tests and confidence intervals |
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24 | (1) |
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24 | (2) |
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26 | (1) |
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27 | (7) |
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34 | (3) |
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Latent failure times: probability distributions |
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37 | (20) |
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Basic probability functions |
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37 | (3) |
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Multivariate survival distributions |
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37 | (1) |
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38 | (2) |
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40 | (6) |
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Marginal vs. sub-distributions |
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46 | (2) |
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48 | (5) |
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50 | (1) |
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51 | (1) |
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52 | (1) |
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53 | (4) |
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Likelihood functions for univariate survival data |
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57 | (26) |
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Discrete and continuous failure times |
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57 | (5) |
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Discrete survival distributions |
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58 | (1) |
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Mixed survival distributions |
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59 | (3) |
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Discrete failure times: estimation |
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62 | (5) |
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Random samples: Parametric estimation |
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62 | (1) |
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Random samples: non-parametric estimation |
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63 | (2) |
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65 | (1) |
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66 | (1) |
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Continuous failure times: random samples |
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67 | (2) |
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The Kaplan-Meier estimator |
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67 | (1) |
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The integrated and cumulative hazard functions |
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68 | (1) |
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Continuous failure times: explanatory variables |
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69 | (7) |
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Cox's proportional hazards model |
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69 | (1) |
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70 | (2) |
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The baseline survivor function |
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72 | (1) |
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73 | (1) |
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Some theory for partial likelihood |
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74 | (2) |
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Discrete failure times again |
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76 | (2) |
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76 | (1) |
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77 | (1) |
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Time-dependent covariates |
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78 | (5) |
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Discrete failure times in Competing Risks |
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83 | (18) |
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Basic probability functions |
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83 | (2) |
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85 | (4) |
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Some examples based on Bernoulli trials |
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89 | (3) |
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92 | (9) |
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93 | (1) |
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Non-parametric estimation from random samples |
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94 | (3) |
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Asymptotic distribution of non-parametric estimators |
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97 | (4) |
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Hazard-based methods for continuous failure times |
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101 | (18) |
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Latent failure times vs. hazard modelling |
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101 | (1) |
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Some examples of hazard modelling |
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102 | (4) |
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Non-parametric methods for random samples |
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106 | (7) |
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The Kaplan-Meier estimator |
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106 | (3) |
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109 | (2) |
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111 | (2) |
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Proportional hazards and partial likelihood |
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113 | (6) |
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The proportional hazards model |
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113 | (1) |
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114 | (2) |
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The baseline survivor functions |
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116 | (1) |
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117 | (2) |
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Latent failure times: identifiability crises |
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119 | (24) |
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119 | (3) |
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More general identifiability results |
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122 | (8) |
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130 | (4) |
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134 | (3) |
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137 | (2) |
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Censoring of survival data |
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139 | (2) |
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Parametric identifiability |
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141 | (2) |
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Martingale counting processes in survival data |
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143 | (24) |
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143 | (1) |
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Back to basics: probability spaces and conditional expectation |
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144 | (3) |
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147 | (1) |
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148 | (3) |
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148 | (2) |
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150 | (1) |
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151 | (2) |
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153 | (1) |
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154 | (5) |
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154 | (1) |
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155 | (2) |
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157 | (1) |
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158 | (1) |
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Non-parametric estimation |
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159 | (2) |
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159 | (1) |
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160 | (1) |
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161 | (2) |
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163 | (2) |
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Intensity models and time-dependent covariates |
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163 | (1) |
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Proportional hazards model |
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164 | (1) |
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164 | (1) |
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165 | (2) |
Appendix 1 Numerical maximisation of likelihood functions |
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167 | (4) |
Appendix 2 Bayesian computation |
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171 | (2) |
Bibliography |
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173 | (10) |
Index |
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183 | |