我有以下模型。数据文件在：https ://drive.google.com/open?id=1_H6YZbdesK7pk5H23mZtp5KhVRKz0Ozl
library(nlme)
library(lme4)
library(car)
library(carData)
library(emmeans)
library(ggplot2)
library(Matrix)
library(multcompView)
datos_weight <- read.csv2("D:/investigacion/publicaciones/articulos-escribiendo/pennisetum/pennisetum-agronomicas/data_weight.csv",header=T, sep = ";", dec = ",")
parte_fija_3 <- formula(weight_DM
~ Genotypes
+ Age
+ I(Age^2)
+ Genotypes*Age
+ Genotypes*I(Age^2))
heterocedasticidad_5 <- varComb(varExp(form = ~fitted(.)))
correlacion_4 <- corCompSymm(form = ~ 1|Block/Genotypes)
modelo_43 <- gls(parte_fija_3,
weights = heterocedasticidad_5,
correlation = correlacion_4,
na.action = na.omit,
data = datos_weight)
anova(modelo_43)
#response
Denom. DF: 48
numDF F-value p-value
(Intercept) 1 597.3828 <.0001
Genotypes 3 2.9416 0.0424
Age 1 471.6933 <.0001
I(Age^2) 1 22.7748 <.0001
Genotypes:Age 3 5.9425 0.0016
Genotypes:I(Age^2) 3 0.7544 0.5253
现在我想用置信区间和数据绘制回归模型，为每个基因型分开。我已经使用ggplot2并绘制了数据，但我无法添加带有置信区间的回归模型。
library(ggplot2)
rango_X <- c(30,90) #x axis
rango_Y <- c(0,175) #y axis
ggplot(datos_weight, aes(x = Age, y = weight_DM)) +
geom_point() +
xlab("Age") +
ylab("Dry matter") +
xlim(rango_X) +
ylim(rango_Y) +
facet_wrap(~ Genotypes, ncol = 2)
图表如下：
对于相同数据的下一次分析，与二次年龄没有交互：Genotypes*I(Age^2)，您将如何将具有置信区间的回归模型添加到图表中？
parte_fija_3 <- formula(weight_DM
~ Genotypes
+ Age
+ I(Age^2)
+ Genotypes*Age)
#+ Genotypes*I(Age^2))
> anova(modelo_44)
Denom. DF: 51
numDF F-value p-value
(Intercept) 1 609.3684 <.0001
Genotypes 3 3.7264 0.0169
Age 1 479.0973 <.0001
I(Age^2) 1 21.9232 <.0001
Genotypes:Age 3 6.4184 0.0009
的线性斜率modelo_44是：
(tendencias_em_lin <- emtrends(modelo_44,
"Genotypes",
var = "Age"))
Genotypes Age.trend SE df lower.CL upper.CL
C 1.613619 0.1723451 51 1.267622 1.959616
E 1.665132 0.2024104 51 1.258776 2.071488
K 1.888587 0.2001627 51 1.486744 2.290430
M 1.059897 0.1205392 51 0.817905 1.301890
二次斜率是？
(tendencias_em_quad <- emtrends(modelo_44,
"Genotypes",
var = "I(Age^2)"))
Genotypes I(Age^2).trend SE df lower.CL upper.CL
C 0.013379926 0.0014290639 51 0.010510961 0.01624889
E 0.013807066 0.0016783618 51 0.010437614 0.01717652
K 0.015659927 0.0016597235 51 0.012327893 0.01899196
M 0.008788536 0.0009994958 51 0.006781965 0.01079511
Confidence level used: 0.95
或摘要中的估计：I(Age^2) = -0.01511？我相信所有基因型的斜率都是恒定的，因为Genotypes*I(Age^2)相互作用尚未经过测试modelo_44：
summary(modelo_44)
Generalized least squares fit by REML
Model: parte_fija_3
....
Coefficients:
Value Std.Error t-value p-value
(Intercept) -73.32555 11.236777 -6.525496 0.0000
GenotypesE 7.22267 9.581979 0.753776 0.4544
GenotypesK -9.83285 9.165962 -1.072757 0.2884
GenotypesM 17.87000 8.085229 2.210203 0.0316
Age 3.43593 0.450041 7.634687 0.0000
I(Age^2) -0.01511 0.004065 -3.717475 0.0005
GenotypesE:Age 0.05151 0.246724 0.208788 0.8354
GenotypesK:Age 0.27497 0.241923 1.136595 0.2610
GenotypesM:Age -0.55372 0.195398 -2.833808 0.0066
...
问题
ggplot2如果我必须为模型绘图，如何在单独的图表中添加具有置信区间和每个基因型数据的回归模型，例如呈现的图表，使用或其他选项：modelo_43和modelo_44？- 我是否用
emtrendsfor正确计算了二次斜率的估计值modelo_44，它是如何正确的？
非常感谢你的回复