我正在尝试绘制 4 个不同回归模型的置信区间点须图。
数据可用here https://figshare.com/s/ace5b44bc12394a7c46d.
#first importing data
Q1<-read.table("~/Q1.txt", header=T)
# Optionally, read in data directly from figshare.
# Q1 <- read.table("https://ndownloader.figshare.com/files/13283882?private_link=ace5b44bc12394a7c46d", header=TRUE)
library(dplyr)
#splitting into female and male
female<-Q1 %>%
filter(sex=="F")
male<-Q1 %>%
filter(sex=="M")
library(lme4)
#Female models
#poisson regression
ab_f_LBS= lmer(LBS ~ ft + grid + (1|byear), data = subset(female))
#negative binomial regression
ab_f_surv= glmer.nb(age ~ ft + grid + (1|byear), data = subset(female), control=glmerControl(tol=1e-6,optimizer="bobyqa",optCtrl=list(maxfun=1e19)))
#Male models
#poisson regression
ab_m_LBS= lmer(LBS ~ ft + grid + (1|byear), data = subset(male))
#negative binomial regression
ab_m_surv= glmer.nb(age ~ ft + grid + (1|byear), data = subset(male), control=glmerControl(tol=1e-6,optimizer="bobyqa",optCtrl=list(maxfun=1e19)))
然后我只想绘制两个变量（ft2 and gridSU）来自每个模型。
ab_f_LBS <- tidy(ab_f_LBS) %>% filter(!grepl('sd_Observation.Residual', term)) %>% filter(!grepl('byear', group))
ab_m_LBS <- tidy(ab_m_LBS) %>% filter(!grepl('sd_Observation.Residual', term)) %>% filter(!grepl('byear', group))
ab_f_surv <- tidy(ab_f_surv) %>% filter(!grepl('sd_Observation.Residual', term)) %>% filter(!grepl('byear', group))
ab_m_surv <- tidy(ab_m_surv) %>% filter(!grepl('sd_Observation.Residual', term)) %>% filter(!grepl('byear', group))
然后我准备制作点须图。
#required packages
library(dotwhisker)
library(broom)
dwplot(list(ab_f_LBS, ab_m_LBS, ab_f_surv, ab_m_surv),
vline = geom_vline(xintercept = 0, colour = "black", linetype = 2),
dodge_size=0.2,
style="dotwhisker") %>% # plot line at zero _behind_ coefs
relabel_predictors(c(ft2= "Immigrants",
gridSU = "Grid (SU)")) +
theme_classic() +
xlab("Coefficient estimate (+/- CI)") +
ylab("") +
scale_color_manual(values=c("#000000", "#666666", "#999999", "#CCCCCC"),
labels = c("Female LRS", "Male LRS", "Female survival", "Male survival"),
name = "First generation models") +
theme(axis.title=element_text(size=10),
axis.text.x = element_text(size=10),
axis.text.y = element_text(size=12, angle=90, hjust=.5),
legend.position = c(0.7, 0.8),
legend.justification = c(0, 0),
legend.title=element_text(size=12),
legend.text=element_text(size=10),
legend.key = element_rect(size = 0.1),
legend.key.size = unit(0.5, "cm"))
我遇到这个问题：
- 错误信息：
Error in psych::describe(x, ...) : unused arguments (conf.int = TRUE, conf.int = TRUE)。当我尝试仅使用 1 个模型时（即dwplot(ab_f_LBS)它有效，但是一旦我添加另一个模型，我就会收到此错误消息。
如何在同一个点须图上绘制 4 个回归模型？
Update
结果traceback():
> traceback()
14: stop(gettextf("cannot coerce class \"%s\" to a data.frame", deparse(class(x))),
domain = NA)
13: as.data.frame.default(x)
12: as.data.frame(x)
11: tidy.default(x, conf.int = TRUE, ...)
10: broom::tidy(x, conf.int = TRUE, ...)
9: .f(.x[[i]], ...)
8: .Call(map_impl, environment(), ".x", ".f", "list")
7: map(.x, .f, ...)
6: purrr::map_dfr(x, .id = "model", function(x) {
broom::tidy(x, conf.int = TRUE, ...)
})
5: eval(lhs, parent, parent)
4: eval(lhs, parent, parent)
3: purrr::map_dfr(x, .id = "model", function(x) {
broom::tidy(x, conf.int = TRUE, ...)
}) %>% mutate(model = if_else(!is.na(suppressWarnings(as.numeric(model))),
paste("Model", model), model))
2: dw_tidy(x, by_2sd, ...)
1: dwplot(list(ab_f_LBS, ab_m_LBS, ab_f_surv, ab_m_surv), effects = "fixed",
by_2sd = FALSE)
这是我的会话信息：
> sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: OS X El Capitan 10.11.6
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib
locale:
[1] en_CA.UTF-8/en_CA.UTF-8/en_CA.UTF-8/C/en_CA.UTF-8/en_CA.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] dotwhisker_0.5.0 broom_0.5.0 broom.mixed_0.2.2
[4] glmmTMB_0.2.2.0 lme4_1.1-18-1 Matrix_1.2-14
[7] bindrcpp_0.2.2 forcats_0.3.0 stringr_1.3.1
[10] dplyr_0.7.6 purrr_0.2.5 readr_1.1.1
[13] tidyr_0.8.1 tibble_1.4.2 ggplot2_3.0.0
[16] tidyverse_1.2.1 lubridate_1.7.4 devtools_1.13.6
loaded via a namespace (and not attached):
[1] ggstance_0.3.1 tidyselect_0.2.5 TMB_1.7.14 reshape2_1.4.3
[5] splines_3.5.1 haven_1.1.2 lattice_0.20-35 colorspace_1.3-2
[9] rlang_0.2.2 pillar_1.3.0 nloptr_1.2.1 glue_1.3.0
[13] withr_2.1.2 modelr_0.1.2 readxl_1.1.0 bindr_0.1.1
[17] plyr_1.8.4 munsell_0.5.0 gtable_0.2.0 cellranger_1.1.0
[21] rvest_0.3.2 coda_0.19-2 memoise_1.1.0 Rcpp_0.12.19
[25] scales_1.0.0 backports_1.1.2 jsonlite_1.5 hms_0.4.2
[29] digest_0.6.18 stringi_1.2.4 grid_3.5.1 cli_1.0.1
[33] tools_3.5.1 magrittr_1.5 lazyeval_0.2.1 crayon_1.3.4
[37] pkgconfig_2.0.2 MASS_7.3-50 xml2_1.2.0 assertthat_0.2.0
[41] minqa_1.2.4 httr_1.3.1 rstudioapi_0.8 R6_2.3.0
[45] nlme_3.1-137 compiler_3.5.1
