README.md

In perlatex/easyuse: A Package to make social statistics more easy and more tidyverse

easyuse

The goal of easyuse is to make social statistics more easy and more tidyverse.

Installation

You can install the development version of easyuse with:

devtools::install_github("perlatex/easyuse")

Example

This is a basic example:

1) For several test scores, the random effects of the test results are assessed using lme4::lmer(score_post ~ 1 + score_pre + (1 | effect)) function

library(tidyverse)

library(easyuse)
data(chengdu)

chengdu %>% get_ran_vals(
  .var_school = school,
  .var_class = class,
  .var_score_pre = score_pre,
  .var_score_post = score_post,
  effects = "class"
)

2) Given a cutoff-value for each variables of data.frame, in order to obtain deprivation data.frame,

df <- tribble(
   ~id, ~x, ~y, ~z, ~g,
   #--|--|--|--|--
   "a", 13.1, 14, 4, 1,
   "b", 11.2, 7, 5, 0,
   "c", 12.5, 10, 1, 0,
   "d", 20, 11, 3, 1
   )

cutoffs <- c(x = 13, y = 12, z = 3)

Generally, we can using mutate() + if_else()

df %>%
  mutate(x = if_else(x < cutoffs$x, 1, 0)) %>%
  mutate(y = if_else(y < cutoffs$y, 1, 0)) %>%
  mutate(z = if_else(z < cutoffs$z, 1, 0))

or using pivot_longer() and then pivot_wider()

df %>%
  pivot_longer(cols = x:z, 
               names_to = "var", 
               values_to = "val") %>%
  mutate(below_cutoff = as.integer(val < cutoffs[var])) %>% 
  select(id, g, var, below_cutoff) %>%
  pivot_wider(names_from = var, values_from = below_cutoff)

Of course, we can write more intuitively

df %>%
   cutoffs_modify_at(.vars = c(x, y), cutoffs = c(x = 13, y = 12))

# A tibble: 4 x 5
  id        x     y     z     g
  <chr> <dbl> <dbl> <dbl> <dbl>
1 a         0     0     4     1
2 b         0     1     5     0
3 c         1     1     1     0
4 d         0     1     3     1

3) Calculate the rowwise weighted mean or sum for columns selected in data.frame

weights <- c(
   x = 0.25,
   y = 0.25,
   z = 0.25,
   g = 0.25
 )

df %>% 
  add_weighted_sum(x:g, .name = "wt_sum", .weights = weights)

# A tibble: 4 x 6
  id        x     y     z     g wt_mean
  <chr> <dbl> <dbl> <dbl> <dbl>   <dbl>
1 a      13.1    14     4     1    8.02
2 b      11.2     7     5     0    5.8 
3 c      12.5    10     1     0    5.88
4 d      20      11     3     1    8.75



df %>%
  add_weighted_mean(x:g, .name = "wt_mean", .weights = weights)
# A tibble: 4 x 6
  id        x     y     z     g wt_mean
  <chr> <dbl> <dbl> <dbl> <dbl>   <dbl>
1 a      13.1    14     4     1    2.01
2 b      15.2     7     5     0    1.7 
3 c      12.5    10     1     0    1.47
4 d      20      11     3     1    2.19

perlatex/easyuse documentation built on April 14, 2020, 5:35 a.m.