问在R中用jtools effect_plot重标预测器EN我试图用jtools包编辑R中预测变量的因子级别的名称，以获得效...
#1chin_plot <- ggplot() +#2geom_point(data, +#3geom_point(data=x_, aes(x= chinde, y=fit), color="blue") +#4geom_line(data=x, aes(x= chinde, y=fit), color="blue") +#5geom_ribbon(data= x , aes(x=c.urchinden, ymin=lower, ymax=upper), alpha=0.3, fill="blue") +#...
Linear model with high dimensional fixed effects Difference-in-difference model with parallel checking plot Instrumental variable model Robust/white standard error Multi-way cluster standard error Instrumental variable model tests, including weak iv test (cragg-dolnald statistics+stock and yogo critical val...
#5 添加具有模型估计置信区间的geom_ribbon#6 根据需要编辑标签!#1chin_plot <- ggplot() +#2geom_point(data , +#3geom_point(data=x_, aes(x= chinde, y=fit), color="blue") +#4geom_line(data=x, aes(x= chinde, y=fit), color="blue") +#5geom_ribbon(data= x , aes(x=c.urchind...
plot(mod) 点击标题查阅往期内容 R语言 线性混合效应模型实战案例 左右滑动查看更多 01 02 03 04 效应大小的格式化图: 让我们更改轴标签和标题。 # 注意:轴标签应按从下到上的顺序排列。 # 要查看效应大小和p值,设置show.values和show.p= TRUE。只有当效应大小的值过大时,才会显示P值。
plot(mod) 点击标题查阅往期内容 R语言 线性混合效应模型实战案例 左右滑动查看更多 01 02 03 04 效应大小的格式化图: 让我们更改轴标签和标题。 # 注意:轴标签应按从下到上的顺序排列。# 要查看效应大小和p值,设置show.values和show.p= TRUE。只有当效应大小的值过大时,才会显示P值。title="草食动物对珊瑚...
chin_plot 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. 最受欢迎的见解 1.基于R语言的lmer混合线性回归模型 2.R语言用Rshiny探索lme4广义线性混合模型(GLMM)和线性混合模型(LMM) ...
pred ='estress',estMethod ="bootstrap",test=T,ci=T,estPlot =T, label =TRUE, paths =TRUE, pm =TRUE) results 结果2: MEDIATION MediationEstimates ──────────────────────────────────...
PlotsOfData is inspired by BoxPlotR. See this link for background information on boxplots. The code for the shiny app is partially derived from ggplotGUI by Gert Stulp The colorblind safe palettes were developed by Paul Tol. The display of bootstrap distributions is inspired by work of Ada...
#create a dose-response curvescenario%>% dose_response()->drchead(drc)#> endpoint mf effect#> 1 L 3.812500 0.009915394#> 2 L 4.799653 0.013954569#> 3 L 6.042405 0.019597765#> 4 L 7.606938 0.027459877#> 5 L 9.576567 0.038357524#> 6 L 12.056184 0.053336214#plot the dose-response curveplot(...