使用 logistf 对象绘制带有误差线的图

Question

我最初使用 glm 包做了一个逻辑模型，但想校正分离，所以我使用了 logistf 函数，现在我正在尝试重做我的绘图。我不确定如何使用 logistf 对象绘制如下图所示的图。很多包似乎不支持它，我试过使用 sjPlot 包的 plot_model() 函数，它为预测概率绘制一个点，但不添加误差线，因为它会自动使用glm 对象。我怎样才能解决这个问题？是否有另一个包可以使这更容易，或者有没有办法手动添加错误栏？

我希望添加误差线的绘图代码是：

sjPlot::plot_model(lr3, type="int", mdrt.values = "meansd", show.values = TRUE, value.offset = .3)

我的模型 lr3 的输出是：

logistf(formula = foodbank_cv ~ wave + ff_country + relevel(race_grp, 
    ref = "White") + sex_cv + age_r + relevel(numchildren, 
    ref = "None") + wave * ff_hcondhas + relevel(carer, 
    ref = "Not") + sempderived + wave * cd_ff_furlough + 
    log(ff_hours) + qual + num + relevel(keyworksector, ref = "Not keyworker") + 
    ca_clinvuln_dv + freemeals + ca_blbenefits1 + log(hhincome_week), 
    data = data, firth = TRUE, family = binomial(link = "logit"))

Model fitted by Penalized ML
Coefficients:
                                                                         coef   se(coef)  lower 0.95  upper 0.95        Chisq            p method
(Intercept)                                                      -5.237542354 0.46736532 -6.23016284 -4.30807241          Inf 0.000000e+00      2
wave5                                                            -0.377956413 0.32598420 -1.07410577  0.28545651 1.232122e+00 2.669947e-01      2
wave7                                                            -0.929934987 0.40813067 -1.84652632 -0.12926473 5.260388e+00 2.181615e-02      2
ff_country2                                                      -0.118780142 0.33317501 -0.86893024  0.51197342 1.196576e-01 7.294061e-01      2
ff_country3                                                       0.393456771 0.25097814 -0.15010616  0.88210537 2.077828e+00 1.494527e-01      2
ff_country4                                                      -0.219066153 0.43493435 -1.23008781  0.57774984 2.481153e-01 6.184053e-01      2
relevel(race_grp, ref = "White")Asian or Asian British            0.882833792 0.22906054  0.39628625  1.33641305 1.183859e+01 5.801581e-04      2
relevel(race_grp, ref = "White")Black or Black British            1.759374627 0.27942672  1.16321835  2.29702048 2.678592e+01 2.272869e-07      2
relevel(race_grp, ref = "White")Mixed                             1.786978145 0.27773294  1.19285979  2.32350705 2.763841e+01 1.462461e-07      2
relevel(race_grp, ref = "White")Other                            -0.345106379 1.38712570 -5.19048868  1.62733736 6.509258e-02 7.986208e-01      2
ff_hcondhas                                                       0.691244774 0.26776923  0.14697164  1.25269746 6.228205e+00 1.257311e-02      2

Method: 1-Wald, 2-Profile penalized log-likelihood, 3-None

我用来制作饥饿和种族情节的代码。我做了一些手动编辑以使其看起来更好，但这是我理想中希望我的情节看起来像的东西：

plot_model(model12, type = "pred", terms = c("race_grp"), mdrt.values = "meansd", axis.textsize = .3, wrap.labels = 5)+ theme_sjplot2() + scale_color_sjplot("simply") + ggplot2::labs(title= "Predicted probabilities of Hunger", x= "Race", y="Percentage")

Answer 1

我找到了解决此问题的方法，但不是使用 logistf 包。如果以后有人想知道这个问题的答案，我的建议是使用 brglm 包。我已经检查过，brglm 包的结果与 logistf 包的结果完全相同。这就是我重新创建上面发布的饥饿情节的方式：

hi2<- brglm(formula= hungry_cv~ wave + ff_country + race_grp + sex_cv + age_r + numchildren + wave*ff_hcondhas + carer + sempderived + wave*cd_ff_furlough + log(ff_hours) + qual + num + keyworksector + ca_clinvuln_dv + freemeals + ca_blbenefits1 + log(hhincome_week), data=data, family=binomial(logit), method = "brglm.fit", pl = TRUE)
racehunger<- plot_model(hi2, type = "pred", terms = c("race_grp"), mdrt.values = "meansd", axis.textsize = .3, wrap.labels = 5, show.values = TRUE)+ theme_sjplot2() + ggplot2::labs(title= "Predicted probabilities of Hunger", x= "Race", y="Percentage")
racehunger

png(file="racehunger.png", units="in", width=11, height=8.5, res=300)
print(racehunger)
dev.off()

代码的输出是：

我个人对结果非常满意。

使用 logistf 对象绘制带有误差线的图

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