epi_stats_corr_rename: Rename variables from melted triangles and convert to factors

In AntonioJBT/episcout: Quickly Clean, Explore and Visualise Large Epidemiological Datasets

Rename variables from melted triangles and convert to factors

Description

Rename variables from melted triangles and convert to factors for plotting. Requires correlation matrices with r and p-values with columns named 'Var1' and 'Var2'. The output of epi_stats_corr_triangle() can be used as input. Variables are converted to factors and re-labelled Values are rounded to digits (default is 2 so that they fit in the heatmap). The output can be used for prettier plotting.

Usage

epi_stats_corr_rename(
  r_vals = "melted_triangles$cormat_melted_triangle_r",
  p_vals = "melted_triangles$cormat_melted_triangle_pval",
  vars_list = vars_list,
  var_labels = var_labels,
  digits = 2
)

Arguments

r_vals	Correlation values in melted (long) format. Default is melted_triangles$cormat_melted_triangle_r
p_vals	p-values from correlations in melted (long) format. Default is melted_triangles$cormat_melted_triangle_pval
vars_list	List of variables to rename from 'Var1' and 'Var2'. Default is vars_list
var_labels	List of labels to use for renaming values from 'Var1' and 'Var2'. vars_list and var_labels must match by position. Default is var_labels
digits	Rounding integer for correlation and p-values. Default is 2

Value

Returns a list object melted_triangles containing the lower triangle of the correlation matrix (cormat) with the correlation (cormat_melted_triangle_r) and p-values (cormat_melted_triangle_pval) with the variables 'Var1' and 'Var2' converted to factors and re-labelled.

Note

vars_list and var_labels must match by position.

Author(s)

Antonio Berlanga-Taylor <\url{https://github.com/AntonioJBT/episcout}>

See Also

epi_stats_corr, epi_stats_corr_triangle, epi_plot_heatmap, epi_plot_heatmap_triangle, rcorr.

Examples

## Not run: 
df <- data.frame(var_id = rep(1:(n / 2), each = 2),
var_to_rep = rep(c("Pre", "Post"), n / 2),
x = rnorm(n),
y = rbinom(n, 1, 0.50),
z = rpois(n, 2)
)
epi_clean_count_classes(df)
df_corr <- df %>%select_if(~ epi_clean_cond_numeric(.))
df_corr <- df_corr[, -1] # exclude var_id
cormat_all <- epi_stats_corr(df_corr, method = 'pearson')
melted_triangles <- epi_stats_corr_triangle(cormat = cormat_all$cormat)
melted_triangles
vars_list <- c('x', 'y', 'z')
var_labels <- c('numeric', 'binomial', 'poisson')
renamed_triangles <- epi_stats_corr_rename(melted_triangles$cormat_melted_triangle_r,
                                           melted_triangles$cormat_melted_triangle_pval,
                                           vars_list = vars_list,
                                           var_labels = var_labels
                                           )
renamed_triangles

## End(Not run)

AntonioJBT/episcout documentation built on Dec. 1, 2024, 4:07 a.m.