test_html

descr(iris)

Variables	Total	p
	(N=150)
Sepal.Length
N	150	<0.001tt1
mean	5.8
sd	0.83
median	5.8
Q1 - Q3	5.1 – 6.4
min - max	4.3 – 7.9
Sepal.Width
N	150	<0.001tt1
mean	3.1
sd	0.44
median	3
Q1 - Q3	2.8 – 3.3
min - max	2 – 4.4
Petal.Length
N	150	<0.001tt1
mean	3.8
sd	1.8
median	4.3
Q1 - Q3	1.6 – 5.1
min - max	1 – 6.9
Petal.Width
N	150	<0.001tt1
mean	1.2
sd	0.76
median	1.3
Q1 - Q3	0.3 – 1.8
min - max	0.1 – 2.5
Species
setosa	50 (33%)	>0.999chi1
versicolor	50 (33%)
virginica	50 (33%)
tt1 Student’s one-sample t-test
chi1 Chi-squared goodness-of-fit test

descr(
  iris,
  "Species",
  group_labels = list(setosa = "My custom group label"),
  var_options = list(Sepal.Length = list(label = "My custom variable label"))
)

Variables	My custom group label	versicolor	virginica	Total	p
	(N=50)	(N=50)	(N=50)	(N=150)
My custom variable label
N	50	50	50	150	<0.001F
mean	5	5.9	6.6	5.8
sd	0.35	0.52	0.64	0.83
median	5	5.9	6.5	5.8
Q1 - Q3	4.8 – 5.2	5.6 – 6.3	6.2 – 6.9	5.1 – 6.4
min - max	4.3 – 5.8	4.9 – 7	4.9 – 7.9	4.3 – 7.9
Sepal.Width
N	50	50	50	150	<0.001F
mean	3.4	2.8	3	3.1
sd	0.38	0.31	0.32	0.44
median	3.4	2.8	3	3
Q1 - Q3	3.2 – 3.7	2.5 – 3	2.8 – 3.2	2.8 – 3.3
min - max	2.3 – 4.4	2 – 3.4	2.2 – 3.8	2 – 4.4
Petal.Length
N	50	50	50	150	<0.001F
mean	1.5	4.3	5.6	3.8
sd	0.17	0.47	0.55	1.8
median	1.5	4.3	5.5	4.3
Q1 - Q3	1.4 – 1.6	4 – 4.6	5.1 – 5.9	1.6 – 5.1
min - max	1 – 1.9	3 – 5.1	4.5 – 6.9	1 – 6.9
Petal.Width
N	50	50	50	150	<0.001F
mean	0.25	1.3	2	1.2
sd	0.11	0.2	0.27	0.76
median	0.2	1.3	2	1.3
Q1 - Q3	0.2 – 0.3	1.2 – 1.5	1.8 – 2.3	0.3 – 1.8
min - max	0.1 – 0.6	1 – 1.8	1.4 – 2.5	0.1 – 2.5
F F-test (ANOVA)

descr(
  iris,
  "Species",
  group_labels = list(setosa = "My custom group label"),
  var_options = list(Sepal.Length = list(label = "My custom variable label")),
  format_options=list(caption="Test Caption")
)

Test Caption

Variables	My custom group label	versicolor	virginica	Total	p
	(N=50)	(N=50)	(N=50)	(N=150)
My custom variable label
N	50	50	50	150	<0.001F
mean	5	5.9	6.6	5.8
sd	0.35	0.52	0.64	0.83
median	5	5.9	6.5	5.8
Q1 - Q3	4.8 – 5.2	5.6 – 6.3	6.2 – 6.9	5.1 – 6.4
min - max	4.3 – 5.8	4.9 – 7	4.9 – 7.9	4.3 – 7.9
Sepal.Width
N	50	50	50	150	<0.001F
mean	3.4	2.8	3	3.1
sd	0.38	0.31	0.32	0.44
median	3.4	2.8	3	3
Q1 - Q3	3.2 – 3.7	2.5 – 3	2.8 – 3.2	2.8 – 3.3
min - max	2.3 – 4.4	2 – 3.4	2.2 – 3.8	2 – 4.4
Petal.Length
N	50	50	50	150	<0.001F
mean	1.5	4.3	5.6	3.8
sd	0.17	0.47	0.55	1.8
median	1.5	4.3	5.5	4.3
Q1 - Q3	1.4 – 1.6	4 – 4.6	5.1 – 5.9	1.6 – 5.1
min - max	1 – 1.9	3 – 5.1	4.5 – 6.9	1 – 6.9
Petal.Width
N	50	50	50	150	<0.001F
mean	0.25	1.3	2	1.2
sd	0.11	0.2	0.27	0.76
median	0.2	1.3	2	1.3
Q1 - Q3	0.2 – 0.3	1.2 – 1.5	1.8 – 2.3	0.3 – 1.8
min - max	0.1 – 0.6	1 – 1.8	1.4 – 2.5	0.1 – 2.5
F F-test (ANOVA)

Tooth2 <- ToothGrowth
Tooth2$categorical <- factor(sample(c("a", "b"), nrow(Tooth2), TRUE))
descr(Tooth2, "supp")

Variables	OJ	VC	Total	p	CI
	(N=30)	(N=30)	(N=60)
len
N	30	30	60	0.061tt2	[-0.17, 7.6]t
mean	21	17	19
sd	6.6	8.3	7.6
median	23	16	19
Q1 - Q3	15 – 26	11 – 23	13 – 25
min - max	8.2 – 31	4.2 – 34	4.2 – 34
dose
N	30	30	60	>0.999tt2	[-0.33, 0.33]t
mean	1.2	1.2	1.2
sd	0.63	0.63	0.63
median	1	1	1
Q1 - Q3	0.5 – 2	0.5 – 2	0.5 – 2
min - max	0.5 – 2	0.5 – 2	0.5 – 2
categorical
a	11 (37%)	15 (50%)	26 (43%)	0.297chi2	[-0.39, 0.12]PWa
b	19 (63%)	15 (50%)	34 (57%)
tt2 Welch’s two-sample t-test
chi2 Pearson’s chi-squared test
t CI for difference in means derived from the t-distribution
PWa CI for difference in proportions derived from a normal (“Wald”) approximation