Question

我正在使用flexsurvreg包中的flexsurv，以便将Gompertz模型与生存数据相匹配。每个参数的一个分类和一个连续协变量的示例如下：

library(survival)
library(flexsurv)
Call:
flexsurvreg(formula = Surv(time, status) ~ sex + shape(ph.ecog), 
data = lung, dist = "gompertz")

Estimates: 
                data mean  est        L95%       U95%       se         exp(est)     L95%       U95%     
shape                  NA   0.000659  -0.000210   0.001527   0.000443         NA         NA         NA
rate                   NA   0.003355   0.002042   0.005512   0.000850         NA         NA         NA
sex              1.396476  -0.525441  -0.852719  -0.198163   0.166982   0.591294   0.426254   0.820236
shape(ph.ecog)   0.951542   0.000937   0.000375   0.001498   0.000287   1.000937   1.000375   1.001500

N = 227,  Events: 164,  Censored: 63
Total time at risk: 69522
Log-likelihood = -1139.932, df = 4
AIC = 2287.864


par$coefficients
shape          rate          sex            shape(ph.ecog) 
0.0006588492  -5.6973226550  -0.5254411364   0.0009368314

请注意，摘要中的费率字词与par$coefficients调用之间的差异是后者显示为前者的自然对数

从小插图 - https://cran.r-project.org/web/packages/flexsurv/flexsurv.pdf - Gompertz Hazard函数定义为 -

Gompertz distribution with shape parameter a and rate parameter b has hazard function H(x: a, b) = b.e^{ax}

我的问题是，如何将协变量应用于形状和速率参数以推导出新的危险函数？

新形状参数是shape_new = shape + ph.ecog_value(between 1-5)*shape(ph.ecog) = 0.0006588492 + (some value between 1 and 5)*0.0009368314而新费率是rate_new = rate + sex = -5.6973226550 - 0.5254411364（根据我之前示例中的变量）？

注意 - 这个先前的问题是相关的，但它并不涉及在形状/速率参数中包含协变量 - Gompertz Aging analysis in R

Flexsurvreg - 应用协变量

0 个答案: