README.md

In graemeblair/stdidx: Tools for creating indices of variables

stdidx

This small package provides a set of simple tools for standardizing variables (based on summary statistics from another variable or a subset, such as a control group in an experiment) and constructing indices of multiple variables. It provides simple mean indexing and inverse covariance-weighted indices.

Installation

Install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("graemeblair/stdidx")

Example

This is a basic example which shows you how to solve a common problem:

library(stdidx)

var1 <- rnorm(100, mean = 0.5, sd = 0.25)
var2 <- rnorm(100, mean = -1, sd = 0.5)
var3 <- rnorm(100, mean = 1, sd = 1)

idx <- idx_mean(var1, var2, var3)
head(idx)
#> [1] -0.1859023  0.4049927  0.4201676  1.2139986 -0.3697271 -0.2082099

stdidx is set up to work with a tidyverse workflow out of the box:

library(dplyr)

df <- tibble(var1, var2, var3)

df %>% mutate(idx_var = idx_mean(var1, var2, var3)) %>% head
#> # A tibble: 6 x 4
#>    var1    var2   var3 idx_var
#>   <dbl>   <dbl>  <dbl>   <dbl>
#> 1 0.843 -0.400  -1.00   -0.186
#> 2 0.359 -0.478   1.33    0.405
#> 3 0.591 -1.50    2.17    0.420
#> 4 0.658 -0.0758  3.06    1.21 
#> 5 0.601 -1.33   -0.377  -0.370
#> 6 0.473 -0.947  -0.151  -0.208

graemeblair/stdidx documentation built on April 19, 2023, 6:48 a.m.