judge_line {crosslag}

Title Determine a linear relationship between x and y by Restricted Cubic Splines(RCS) and plot it

Description

Title Determine a linear relationship between x and y by Restricted Cubic Splines(RCS) and plot it

Usage

judge_line(xname, yname, Data, parm)

Arguments

xname

A character, the name of the x. If there are multiple covariates, they need to be saved in a vector

yname

A character, the name of the y. If there are multiple covariates, they need to be saved in a vector

Data

A dataframe containing data of x and y. The input 'xname' and 'yname' is written in the same way among the 'Data' column names

parm

the number of knots of RCS

Value

A list containing the information of RCS plots. You can use 'ggpubr::ggarrange()' to plot the list. The list is a list of ggplot objects. Each ggplot object is a plot that represents the relationship between one independent variable (from xname) and one dependent variable (from yname). These plots are based on a linear regression model that uses a restricted cubic spline to handle the independent variable. Each plot includes a line of predicted values (solid blue line) and a confidence interval for these predictions (transparent blue area). The title of each plot includes the p-value for non-linearity, as well as the names of the independent and dependent variables.

Examples

data(test_data1)

# Get RCS plots
result <- judge_line(xname="ASI",yname="HDL_C",Data = test_data1,parm = 4)
## Plot an RCS curve graph
ggpubr::ggarrange(result[[1]])

# Simultaneously determining multiple linear relationships
results <- judge_line("ASI",c("HDL_C","LDL_C"),Data = test_data1,parm = 4)
## Plot many RCS curve graphs
## Adjust 'nrow' and 'ncol' according to actual situation
ggpubr::ggarrange(plotlist = results, nrow = 1, ncol = 2)