rreg package

Description

Data visualization for Norwegian Health Quality Registries with R. This package will assist and standardize the visualization of data from the Norwegian Health Quality Registries. The standardization is based on the requirement specified by the Nasjonalt servicemiljø for medisinske kvalitetsregistre.

Author(s)

Yusman Kamaleri <ybkamaleri@gmail.com>

hfdata as sample data for institutions

Description

hfdata is just a randomly created dataset to show how this package works. The centre names are derived from names of towns on the north-eastern part of Borneo.

Usage

hfdata

Format

hfdata consist of several columns:

• inst: The institution names and "Sabah" is the region name

• id: The identification number of the centres

• 2003-2007: The measurement collected yearly based

• case1: Cases normally distributed with mean=60 and SD=30

• case2: Cases normally distributed with mean=20 and SD=2

• extt: Variable with extreme values

• ll: Lower limit for case2

• up: Upper limit for case2

Barplot with explicit data comparison

Description

Create a barplot with the posibility to differentiate a specific item compared to the rest. This is useful in a situation when there is a need to show the total value as compared to each items in the x-axis. A specific example related to the Norwegian Health Registries is when the aggregated value from each health institutions or health regions is compared to the national data.

Usage

regbar(data, x, y, comp, num, aim = NULL, split = NULL, ascending = TRUE,
  title, ylab, col1, col2, col3, flip = TRUE, ...)

Arguments

Examples

# basic usage
library("rreg")
regbar(data = hfdata, x = inst, y = case2)
regbar(hfdata, inst, case2, comp = "Tawau HF")
regbar(hfdata, inst, 2007, comp = "Taw", num = extt)

# split text visualisatio at 5% of max value
regbar(hfdata, inst, 2007, comp = "Taw", split = 0.05)

Barplot with point and table for comparison

Description

Create a barplot with point to visualise comparison. It is also possible to include table to show the value of the plot.

Usage

regcom(data, x, yl, yc, tab = TRUE, title, scale, ascending = TRUE, col1,
  col2, lab1, lab2, num, rotate, leg1, leg2, ...)

Arguments

Examples

library("rreg")
regcom(data = hfdata, x = inst, yl = case2, yc = case1)

# include table
regcom(data = hfdata, x = inst, yl = case2, yc = case1, tab = FALSE)

# keep original order
regcom(data = hfdata, x = inst, yl = case2, yc = case1, scale = "Percentage", ascending = FALSE)

# text for table rotate 10%
regcom(data = hfdata, x = inst, yl = case2, yc = case1, lab1="Tawau", lab2="Negara", rotate=10)

Plot for variability

Description

Create a plot to show uncertainty either by showing the Standard Error of the Mean (SEM) or Confidence Interval (CI). Lower and upper limit should be specified. Figure should also be commented if the variability is a SEM or CI.

Usage

regerr(data, x, y, ll, ul, title, ylab, comp, col1, col2, ascending = TRUE,
  flip = TRUE, ...)

Arguments

Examples

# basic usage
regerr(hfdata, inst, case2, ll, ul)
regerr(hfdata, inst, case2, ll, ul, comp="Sabah")

Line plot to show trend

Description

Create a line plot that can be used to elucidate if trends exit over time.

Usage

regline(data, x, y, grp, title, ylab, colp, digit, ...)

Arguments

Examples

regline(data = yrdata, x=year, y=pros, grp=var)
regline(yrdata, year, pros, var, colp="Set1", digit=1)

Dartboard diagram for precision

Description

Create a dartboard style diagram to visualise precision. The middle point represent complete precision for example the objectives or plans. Imagine it's like a dartboard and the center means 100% precision or it could be completeness/achievement. The standard division of the proportion to show precision allocated in the diagram is 50%, 80% and 100%.

Usage

regrad(data, x, y, long = FALSE, title, size, pct1, pct2, col1, col2, col3,
  ...)

Arguments

Details

These parameters should be specified:

• x-axis 1st column: The names of the different institutions

• y-axis 2nd column: The value to show completeness

Note

The ggplot2 package is required to run this function

Source

hfdata is a sample data which does not derive from a real data

Examples

# basic usage
library("rreg")
regrad(data = hfdata)
regrad(data = hfdata, title = "Plot title", long = TRUE)
regrad(hfdata, y= case1, title="Plot title", size=10, col1="blue", col2="green", col3="yellow")

yrdata is sample data for trends

Description

yrdata is just a sample data to use in example for "regline" function.

Usage

yrdata

Format

yrdata consist of these variables:

• year: List of different years

• var: Variable to be grouped

• N: Number of n for each group

• sum: Total for each year

• pros: Percentage for each group