summary.PHcure: Summary method for PHcure.object
In a-beretta/penPHcure: Variable Selection in PH Cure Model with Time-Varying Covariates
Description
Usage
Arguments
Value
Examples
View source: R/summary.PHcure.R
Description
Produces a summary of a fitted PH cure model
Usage
1
2
Arguments
object
an object of class PHcure.object.
conf.int
a character string indicating the method to compute bootstrapped confidence intervals: "percentile" or "basic". By default conf.int = "basic".
conf.int.level
confidence level. By default conf.int.level = 0.95.
...
ellipsis to pass extra arguments.
Value
An object of class summary.PHcure, a list including the following elements:
N
the sample size (number of individuals).
censoring
the proportion of censored individuals.
K
the number of unique failure times.
isTies
a logical value, equal to TRUE in case of tied event times.
conf.int
a character string indicating the method used to compute the bootstrapped confidence intervals: "percentile", "basic" or "no". The latter is returned when the penPHcure function was called with the argument inference = FALSE.
conf.int.level
confidence level used to compute the bootstrapped confidence intervals.
nboot
the number of bootstrap resamples for the construction of the confidence intervals.
logL
the value of the log-likelihood for the estimated model.
CURE
a matrix with one column containing the estimated regression coefficients in the incidence (cure) component. In case the function penPHcure was called with the argument inference = TRUE, two additional columns for the confidence intervals are provided.
SURV
a matrix where in the first column the estimated regression coefficients in the latency (survival) component. In case the function penPHcure was called with the argument inference = TRUE, two additional columns for the confidence intervals are provided.
Examples
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# For reproducibility
set.seed(12)
# If you use R v3.6 or greater, uncomment the following line
# RNGkind(sample.kind="Rounding")
# Generate some data (for more details type ?penPHcure.simulate in your console)
data <- penPHcure.simulate(N=250)
# Fit standard cure model (without inference)
fit <- penPHcure(Surv(time = tstart,time2 = tstop,
event = status) ~ z.1 + z.2 + z.3 + z.4,
cureform = ~ x.1 + x.2 + x.3 + x.4,data = data)
# Use the summary method to see the results
summary(fit)
#
# ------------------------------------------------------
# +++ PH cure model with time-varying covariates +++
# ------------------------------------------------------
# Sample size: 250
# Censoring proportion: 0.5
# Number of unique event times: 125
# Tied failure times: FALSE
#
# log-likelihood: 74.11
#
# ------------------------------------------------------
# +++ Cure (incidence) coefficients +++
# ------------------------------------------------------
# Estimate
# (Intercept) 0.889668
# x.1 -0.972653
# x.2 -0.051580
# x.3 0.714611
# x.4 0.156169
#
# ------------------------------------------------------
# +++ Survival (latency) coefficients +++
# ------------------------------------------------------
# Estimate
# z.1 0.996444
# z.2 -0.048792
# z.3 -1.013562
# z.4 0.079422
# Fit standard cure model (with inference). nboot = 30 bootstrap resamples
# are used to compute the confidence intervals.
fit2 <- penPHcure(Surv(time = tstart,time2 = tstop,
event = status) ~ z.1 + z.2 + z.3 + z.4,
cureform = ~ x.1 + x.2 + x.3 + x.4,data = data,
inference = TRUE,print.details = FALSE,nboot = 30)
# Use the summary method to see the results
summary(fit2)
#
# ------------------------------------------------------
# +++ PH cure model with time-varying covariates +++
# ------------------------------------------------------
# Sample size: 250
# Censoring proportion: 0.5
# Number of unique event times: 125
# Tied failure times: FALSE
#
# log-likelihood: 74.11
#
# ------------------------------------------------------
# +++ Cure (incidence) coefficient estimates +++
# +++ and 95% confidence intervals * +++
# ------------------------------------------------------
# Estimate 2.5% 97.5%
# (Intercept) 0.889668 0.455975 1.092495
# x.1 -0.972653 -1.414194 -0.503824
# x.2 -0.051580 -0.557843 0.304632
# x.3 0.714611 0.206211 1.081819
# x.4 0.156169 -0.011555 0.464841
#
# ------------------------------------------------------
# +++ Survival (latency) coefficient estimates +++
# +++ and 95% confidence intervals * +++
# ------------------------------------------------------
# Estimate 2.5% 97.5%
# z.1 0.996444 0.750321 1.130650
# z.2 -0.048792 -0.204435 0.073196
# z.3 -1.013562 -1.127882 -0.780339
# z.4 0.079422 -0.100677 0.193522
#
# ------------------------------------------------------
# * Confidence intervals computed by the basic
# bootstrap method, with 30 replications.
# ------------------------------------------------------
# By default, confidence intervals are computed by the basic bootstrap method.
# Otherwise, the user can specify the percentile bootstrap method.
summary(fit2,conf.int = "percentile")
#
# ------------------------------------------------------
# +++ PH cure model with time-varying covariates +++
# ------------------------------------------------------
# Sample size: 250
# Censoring proportion: 0.5
# Number of unique event times: 125
# Tied failure times: FALSE
#
# log-likelihood: 74.11
#
# ------------------------------------------------------
# +++ Cure (incidence) coefficient estimates +++
# +++ and 95% confidence intervals * +++
# ------------------------------------------------------
# Estimate 2.5% 97.5%
# (Intercept) 0.889668 0.686842 1.323362
# x.1 -0.972653 -1.441483 -0.531112
# x.2 -0.051580 -0.407791 0.454684
# x.3 0.714611 0.347404 1.223011
# x.4 0.156169 -0.152503 0.323893
#
# ------------------------------------------------------
# +++ Survival (latency) coefficient estimates +++
# +++ and 95% confidence intervals * +++
# ------------------------------------------------------
# Estimate 2.5% 97.5%
# z.1 0.996444 0.862238 1.242567
# z.2 -0.048792 -0.170779 0.106852
# z.3 -1.013562 -1.246785 -0.899242
# z.4 0.079422 -0.034678 0.259521
#
# ------------------------------------------------------
# * Confidence intervals computed by the percentile
# bootstrap method, with 30 replications.
# ------------------------------------------------------
# By default, a 95% confidence level is used. Otherwise, the user can specify
# another confidence level: e.g. 90%.
summary(fit2,conf.int.level = 0.90)
#
# ------------------------------------------------------
# +++ PH cure model with time-varying covariates +++
# ------------------------------------------------------
# Sample size: 250
# Censoring proportion: 0.5
# Number of unique event times: 125
# Tied failure times: FALSE
#
# log-likelihood: 74.11
#
# ------------------------------------------------------
# +++ Cure (incidence) coefficient estimates +++
# +++ and 90% confidence intervals * +++
# ------------------------------------------------------
# Estimate 5% 95%
# (Intercept) 0.889668 0.467864 1.074423
# x.1 -0.972653 -1.397088 -0.618265
# x.2 -0.051580 -0.527389 0.249460
# x.3 0.714611 0.314140 1.028425
# x.4 0.156169 0.033802 0.436361
#
# ------------------------------------------------------
# +++ Survival (latency) coefficient estimates +++
# +++ and 90% confidence intervals * +++
# ------------------------------------------------------
# Estimate 5% 95%
# z.1 0.996444 0.767937 1.125745
# z.2 -0.048792 -0.158821 0.050965
# z.3 -1.013562 -1.120989 -0.800606
# z.4 0.079422 -0.086063 0.180392
#
# ------------------------------------------------------
# * Confidence intervals computed by the basic
# bootstrap method, with 30 replications.
# ------------------------------------------------------
a-beretta/penPHcure documentation built on Dec. 3, 2019, 5:41 p.m.
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Description Usage Arguments Value Examples
View source: R/summary.PHcure.R
Description
Produces a summary of a fitted PH cure model
Usage
1 2 |
Arguments
object |
an object of class |
conf.int |
a character string indicating the method to compute bootstrapped confidence intervals: |
conf.int.level |
confidence level. By default |
... |
ellipsis to pass extra arguments. |
Value
An object of class summary.PHcure, a list including the following elements:
|
the sample size (number of individuals). |
|
the proportion of censored individuals. |
|
the number of unique failure times. |
|
a logical value, equal to |
|
a character string indicating the method used to compute the bootstrapped confidence intervals: |
|
confidence level used to compute the bootstrapped confidence intervals. |
|
the number of bootstrap resamples for the construction of the confidence intervals. |
|
the value of the log-likelihood for the estimated model. |
|
a matrix with one column containing the estimated regression coefficients in the incidence (cure) component. In case the function |
|
a matrix where in the first column the estimated regression coefficients in the latency (survival) component. In case the function |
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 | # For reproducibility
set.seed(12)
# If you use R v3.6 or greater, uncomment the following line
# RNGkind(sample.kind="Rounding")
# Generate some data (for more details type ?penPHcure.simulate in your console)
data <- penPHcure.simulate(N=250)
# Fit standard cure model (without inference)
fit <- penPHcure(Surv(time = tstart,time2 = tstop,
event = status) ~ z.1 + z.2 + z.3 + z.4,
cureform = ~ x.1 + x.2 + x.3 + x.4,data = data)
# Use the summary method to see the results
summary(fit)
#
# ------------------------------------------------------
# +++ PH cure model with time-varying covariates +++
# ------------------------------------------------------
# Sample size: 250
# Censoring proportion: 0.5
# Number of unique event times: 125
# Tied failure times: FALSE
#
# log-likelihood: 74.11
#
# ------------------------------------------------------
# +++ Cure (incidence) coefficients +++
# ------------------------------------------------------
# Estimate
# (Intercept) 0.889668
# x.1 -0.972653
# x.2 -0.051580
# x.3 0.714611
# x.4 0.156169
#
# ------------------------------------------------------
# +++ Survival (latency) coefficients +++
# ------------------------------------------------------
# Estimate
# z.1 0.996444
# z.2 -0.048792
# z.3 -1.013562
# z.4 0.079422
# Fit standard cure model (with inference). nboot = 30 bootstrap resamples
# are used to compute the confidence intervals.
fit2 <- penPHcure(Surv(time = tstart,time2 = tstop,
event = status) ~ z.1 + z.2 + z.3 + z.4,
cureform = ~ x.1 + x.2 + x.3 + x.4,data = data,
inference = TRUE,print.details = FALSE,nboot = 30)
# Use the summary method to see the results
summary(fit2)
#
# ------------------------------------------------------
# +++ PH cure model with time-varying covariates +++
# ------------------------------------------------------
# Sample size: 250
# Censoring proportion: 0.5
# Number of unique event times: 125
# Tied failure times: FALSE
#
# log-likelihood: 74.11
#
# ------------------------------------------------------
# +++ Cure (incidence) coefficient estimates +++
# +++ and 95% confidence intervals * +++
# ------------------------------------------------------
# Estimate 2.5% 97.5%
# (Intercept) 0.889668 0.455975 1.092495
# x.1 -0.972653 -1.414194 -0.503824
# x.2 -0.051580 -0.557843 0.304632
# x.3 0.714611 0.206211 1.081819
# x.4 0.156169 -0.011555 0.464841
#
# ------------------------------------------------------
# +++ Survival (latency) coefficient estimates +++
# +++ and 95% confidence intervals * +++
# ------------------------------------------------------
# Estimate 2.5% 97.5%
# z.1 0.996444 0.750321 1.130650
# z.2 -0.048792 -0.204435 0.073196
# z.3 -1.013562 -1.127882 -0.780339
# z.4 0.079422 -0.100677 0.193522
#
# ------------------------------------------------------
# * Confidence intervals computed by the basic
# bootstrap method, with 30 replications.
# ------------------------------------------------------
# By default, confidence intervals are computed by the basic bootstrap method.
# Otherwise, the user can specify the percentile bootstrap method.
summary(fit2,conf.int = "percentile")
#
# ------------------------------------------------------
# +++ PH cure model with time-varying covariates +++
# ------------------------------------------------------
# Sample size: 250
# Censoring proportion: 0.5
# Number of unique event times: 125
# Tied failure times: FALSE
#
# log-likelihood: 74.11
#
# ------------------------------------------------------
# +++ Cure (incidence) coefficient estimates +++
# +++ and 95% confidence intervals * +++
# ------------------------------------------------------
# Estimate 2.5% 97.5%
# (Intercept) 0.889668 0.686842 1.323362
# x.1 -0.972653 -1.441483 -0.531112
# x.2 -0.051580 -0.407791 0.454684
# x.3 0.714611 0.347404 1.223011
# x.4 0.156169 -0.152503 0.323893
#
# ------------------------------------------------------
# +++ Survival (latency) coefficient estimates +++
# +++ and 95% confidence intervals * +++
# ------------------------------------------------------
# Estimate 2.5% 97.5%
# z.1 0.996444 0.862238 1.242567
# z.2 -0.048792 -0.170779 0.106852
# z.3 -1.013562 -1.246785 -0.899242
# z.4 0.079422 -0.034678 0.259521
#
# ------------------------------------------------------
# * Confidence intervals computed by the percentile
# bootstrap method, with 30 replications.
# ------------------------------------------------------
# By default, a 95% confidence level is used. Otherwise, the user can specify
# another confidence level: e.g. 90%.
summary(fit2,conf.int.level = 0.90)
#
# ------------------------------------------------------
# +++ PH cure model with time-varying covariates +++
# ------------------------------------------------------
# Sample size: 250
# Censoring proportion: 0.5
# Number of unique event times: 125
# Tied failure times: FALSE
#
# log-likelihood: 74.11
#
# ------------------------------------------------------
# +++ Cure (incidence) coefficient estimates +++
# +++ and 90% confidence intervals * +++
# ------------------------------------------------------
# Estimate 5% 95%
# (Intercept) 0.889668 0.467864 1.074423
# x.1 -0.972653 -1.397088 -0.618265
# x.2 -0.051580 -0.527389 0.249460
# x.3 0.714611 0.314140 1.028425
# x.4 0.156169 0.033802 0.436361
#
# ------------------------------------------------------
# +++ Survival (latency) coefficient estimates +++
# +++ and 90% confidence intervals * +++
# ------------------------------------------------------
# Estimate 5% 95%
# z.1 0.996444 0.767937 1.125745
# z.2 -0.048792 -0.158821 0.050965
# z.3 -1.013562 -1.120989 -0.800606
# z.4 0.079422 -0.086063 0.180392
#
# ------------------------------------------------------
# * Confidence intervals computed by the basic
# bootstrap method, with 30 replications.
# ------------------------------------------------------
|
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