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Step 3. Visualise the sequence ratios

Source: vignettes/a04_Visualise_sequence_ratios.Rmd
a04_Visualise_sequence_ratios.Rmd

Introduction

In this vignette we will explore the functionality and arguments of a set of functions that will help us to understand and visualise the sequence ratio results. In particular, we will delve into the following functions:

This function builds-up on previous functions, such as generateSequenceCohortSet() and summariseSequenceRatios() function (explained in detail in previous vignettes: Step 1. Generate a sequence cohort and Step 2. Obtain the sequence ratios respectively). Hence, we will pick up the explanation from where we left off in the previous vignette.

Recall we had the table intersect in the cdm reference and that the results of sequence ratio could produced as follows (Step 2. Obtain the sequence ratios):

result <- summariseSequenceRatios(cohort = cdm$intersect)

Table output of the sequence ratio results

The function tableSequenceRatios inputs the result from summariseSequenceRatios, the default outputs a gt table.

tableSequenceRatios(result = result)
Index cohort name Variable name Estimate name
Marker cohort name
amoxicillin
GiBleed
aspirin index N (%) 42 (58.30%)
marker N (%) 30 (41.70%)
null SR 1.04
crude SR [CI 95%] 1.40 [0.88 - 2.25]
adjusted SR [CI 95%] 1.34 [0.84 - 2.15]

Modify type

Instead of a gt table, the user may also want to put the sequence ratio results in a flextable table format (the rest of the arguments that we saw for a gt table also applies here):


if (requireNamespace("flextable", quietly = TRUE)) {
  tableSequenceRatios(
    result = result,
    type = "flextable"
  )
}

Index cohort name

Variable name

Estimate name

Marker cohort name

amoxicillin

GiBleed

aspirin

index

N (%)

42 (58.30%)

marker

N (%)

30 (41.70%)

null

SR

1.04

crude

SR [CI 95%]

1.40 [0.88 - 2.25]

adjusted

SR [CI 95%]

1.34 [0.84 - 2.15]

Or a tibble:

tableSequenceRatios(result = result,
                    type = "tibble")
#> # A tibble: 5 × 5
#>   `Data source` `Index cohort name` `Variable name` `Estimate name`
#>   <chr>         <chr>               <chr>           <chr>          
#> 1 GiBleed       aspirin             index           N (%)          
#> 2 GiBleed       aspirin             marker          N (%)          
#> 3 GiBleed       aspirin             null            SR             
#> 4 GiBleed       aspirin             crude           SR [CI 95%]    
#> 5 GiBleed       aspirin             adjusted        SR [CI 95%]    
#> # ℹ 1 more variable:
#> #   `[header_name]Marker cohort name\n[header_level]amoxicillin` <chr>

Plot output of the sequence ratio results

Similarly, we also have plotSequenceRatios() to visualise the results.

plotSequenceRatios(result = result)

By default, it plots both the adjusted sequence ratios (and its CIs) and crude sequence ratios (and its CIs). One may wish to only plot adjusted one like so (note since only adjusted is plotted, only one colour needs to be specified):

Modify onlyASR and colours 

plotSequenceRatios(result = result,
                   onlyASR = T,
                   colours = "black")

One could change the colour like so:

plotSequenceRatios(result = result,
                   onlyASR = T,
                   colours = "red")