One-term models: visualization
Visualize relationship between covariates and response variables.
Load packages, read data and source custom scripts
rm(list = ls())
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(mgcv)
#> Loading required package: nlme
#>
#> Attaching package: 'nlme'
#> The following object is masked from 'package:dplyr':
#>
#> collapse
#> This is mgcv 1.8-31. For overview type 'help("mgcv-package")'.
library(purrr)
library(ggplot2)
path_proj <- day2day::git_path()
path_data <- file.path(path_proj, "data")
path_processed <- file.path(path_data, "processed")
path_modelled <- file.path(path_data, "modelled")
source(file.path(path_proj, "src", "55-mgcv-visualize.R"))
model_data <- readRDS(file.path(path_modelled, "bw-explore-smooths.rds"))
bwdata_model <- fst::read_fst(file.path(path_processed, "bwdata_41_model.fst"))
Visualize exploratory models of birthweight
covar_names <- c(
age = "mother age",
wk_ini = "conception date",
rivwk_conception = "river week of conception",
remoteness = "remoteness",
rur_prop = "proportion of rural population",
prop_tap_toilet = "proportion of population with tap water"
)
data_gams <- model_data %>%
dplyr::select(- formula) %>%
get_data_gams()
data_gams <- map(data_gams, ~ mutate(., covar = covar_names[covar]))
plot_gam_1d(data_gams) +
scale_fill_manual(values = "gray60") +
scale_colour_manual(values = "red") +
facet_wrap(~ covar, scales = "free", ncol = 2) +
theme(legend.position = "none")
Time to execute the task
Only useful when executed with Rscript
.
proc.time()
#> user system elapsed
#> 4.478 0.196 4.690