Getting Started with the `controlcharts` package

Getting Started

Constructing SPC Charts

Consider a basic time-series, comprised of two-years of monthly data:

# Simulate 2 years of monthly data
dat <- data.frame(
  month = seq(as.Date("2024-01-01"), length.out = 24, by = "month"),
  y = rnorm(24)
)

knitr::kable(head(dat))

month	y
2024-01-01	0.0672962
2024-02-01	0.7948403
2024-03-01	1.5177286
2024-04-01	-2.1648999
2024-05-01	-0.2143888
2024-06-01	0.1285904

By default, the spc() function will construct an i-chart (individuals chart; also referred to as an XmR-chart):

spc_chart <- controlcharts::spc(data = dat,
                                numerators = y,
                                keys = month)

The result of the spc() function is a list containing three elements:

• static_plot: a static SVG plot of the SPC chart
• html_plot: an HTML widget containing the interactive SPC chart (for use in Shiny/interactive contexts)
• limits: a data frame containing the calculated control limits

spc_chart$static_plot

# If you are using an interactive environment, you can display the HTML widget:
# spc_chart$html_plot

# Display the control limits
knitr::kable(head(spc_chart$limits), digits = 2)

date	value	target	ll99	ll95	ll68	ul68	ul95	ul99	trend_line
01/01/2024	0.07	-0.14	-2.53	-1.73	-0.93	0.66	1.46	2.25	-0.56
01/02/2024	0.79	-0.14	-2.53	-1.73	-0.93	0.66	1.46	2.25	-0.53
01/03/2024	1.52	-0.14	-2.53	-1.73	-0.93	0.66	1.46	2.25	-0.49
01/04/2024	-2.16	-0.14	-2.53	-1.73	-0.93	0.66	1.46	2.25	-0.45
01/05/2024	-0.21	-0.14	-2.53	-1.73	-0.93	0.66	1.46	2.25	-0.42
01/06/2024	0.13	-0.14	-2.53	-1.73	-0.93	0.66	1.46	2.25	-0.38

Funnel Plot

The same interface is provided for funnel charts. For this example, consider proportion data recorded by 10 organisations:

# Simulate proportion data for 10 organisations
denoms <- sample(100:200, 10)
funnel_data <- data.frame(
  organisation = letters[1:10],
  numerators = rbinom(10, size = denoms, prob = 0.2),
  denominators = denoms
)

knitr::kable(funnel_data)

organisation	numerators	denominators
a	27	170
b	23	122
c	35	178
d	26	184
e	38	161
f	22	105
g	46	190
h	27	121
i	27	137
j	35	197

For funnel plots, the default is a proportions (PR) chart:

funnel_chart <- controlcharts::funnel(data = funnel_data,
                                      numerators = numerators,
                                      denominators = denominators,
                                      keys = organisation)

funnel_chart$static_plot

knitr::kable(funnel_chart$limits, digits = 2)

denominator	group	numerator	value	z	ll99	ll95	ll68	ul68	ul95	ul99	target
105	f	22	20.95	0.36	9.15	12.57	15.85	23.54	27.65	32.71	19.55
121	h	27	22.31	0.75	9.75	13.01	16.10	23.26	27.06	31.74	19.55
122	b	23	18.85	-0.20	9.78	13.03	16.11	23.24	27.03	31.69	19.55
137	i	27	19.71	0.05	10.26	13.37	16.30	23.03	26.59	30.96	19.55
161	e	38	23.60	1.25	10.89	13.81	16.54	22.75	26.02	30.02	19.55
170	a	27	15.88	-1.25	11.09	13.96	16.62	22.66	25.84	29.72	19.55
178	c	35	19.66	0.04	11.26	14.08	16.68	22.59	25.69	29.47	19.55
184	d	26	14.13	-1.97	11.38	14.16	16.73	22.54	25.58	29.30	19.55
190	g	46	24.21	1.55	11.50	14.24	16.77	22.49	25.48	29.13	19.55
197	j	35	17.77	-0.64	11.63	14.33	16.82	22.44	25.37	28.95	19.55