scimple : Tidy Simultaneous Confidence Intervals for Multinomial Proportions

This is a tidy version of the CoinMinD R package with some extra bits tossed in for good measure.

The following functions are implemented:

• scimple_ci: Calculate multiple simultaneous confidence intervals using selected methods (excluding Bayesian methods)
• scimp_bmde: Bayesian Multinomial Dirichlet Model (Equal Prior)
• scimp_bmdu: Bayesian Multinomial Dirichlet Model (Unequal Prior)
• scimp_fs: Fitzpatrick & Scott Confidence Interval
• scimp_goodman: Goodman Confidence Interval
• scimp_qh: Quesenberry & Hurst Confidence Interval
• scimp_sg: Sison & Glaz Confidence Interval
• scimp_wald: Wald Confidence Interval
• scimp_waldcc: Wald Confidence Interval (with continuity correction)
• scimp_wilson: Wilson Confidence Interval

There's also a handy named vector scimple_short_to_long which you can use to expand shorthand method names (e.g. "sg") to long (e.g. "Sison & Glaz").

Installation

devtools::install_github("hrbrmstr/scimple")

Usage

library(scimple)
library(hrbrthemes)
library(tidyverse)

# current verison
packageVersion("scimple")

## [1] '0.1.0'

y <- c(44, 55, 43, 32, 67, 78)
z <- 0.05

scimple_ci(y, z) %>% 
  mutate(method=scimple_short_to_long[method]) -> cis

print(cis)

## # A tibble: 42 × 8
##                 method lower_limit upper_limit     adj_ll    adj_ul   volume inpmat alpha
##                  <chr>       <dbl>       <dbl>      <dbl>     <dbl>    <dbl>  <dbl> <dbl>
## 1  Fitzpatrick & Scott  0.08306258   0.1927995 0.08306258 0.1927995 1.75e-06     44  0.05
## 2  Fitzpatrick & Scott  0.11754534   0.2272823 0.11754534 0.2272823 1.75e-06     55  0.05
## 3  Fitzpatrick & Scott  0.07992778   0.1896647 0.07992778 0.1896647 1.75e-06     43  0.05
## 4  Fitzpatrick & Scott  0.04544502   0.1551819 0.04544502 0.1551819 1.75e-06     32  0.05
## 5  Fitzpatrick & Scott  0.15516289   0.2648998 0.15516289 0.2648998 1.75e-06     67  0.05
## 6  Fitzpatrick & Scott  0.18964565   0.2993826 0.18964565 0.2993826 1.75e-06     78  0.05
## 7              Goodman  0.09468368   0.1966413 0.09468368 0.1966413 1.55e-06     44  0.05
## 8              Goodman  0.12376893   0.2350489 0.12376893 0.2350489 1.55e-06     55  0.05
## 9              Goodman  0.09208527   0.1931040 0.09208527 0.1931040 1.55e-06     43  0.05
## 10             Goodman  0.06412671   0.1535697 0.06412671 0.1535697 1.55e-06     32  0.05
## # ... with 32 more rows

ggplot(cis) +
  geom_segment(aes(x=lower_limit, xend=upper_limit, y=method, yend=method, color=method)) +
  scale_color_ipsum(name=NULL) +
  facet_wrap(~inpmat, scales="free_x") +
  labs(x=NULL, y=NULL, 
       title="Multipe simultaneous confidence intervals",
       subtitle="Note free X scale") +
  theme_ipsum_rc(grid="X", base_size=11) +
  theme(legend.position="bottom")

Test Results

library(scimple)
library(testthat)

date()

## [1] "Sat Mar  4 00:21:15 2017"

test_dir("tests/")

## testthat results ========================================================================================================
## OK: 16 SKIPPED: 0 FAILED: 0
## 
## DONE ===================================================================================================================