tableStack: Tabulation of variables in a stack form
In ems: Epimed Solutions Collection for Data Editing, Analysis, and Benchmark of Health Units
Description
Usage
Arguments
Details
Value
Author(s)
References
Examples
Description
There are two functionalities: Tabulation of variables with the same possible range of distribution and stack into a new table with or without other descriptive statistics or to breakdown distribution of more than one row variables against a column variable
Usage
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
tableStack(
vars,
dataFrame,
minlevel = "auto",
maxlevel = "auto",
count = TRUE,
na.rm = FALSE,
means = TRUE,
medians = FALSE,
sds = TRUE,
decimal = 2,
total = TRUE,
var.labels = TRUE,
var.labels.trunc = 150,
reverse = FALSE,
vars.to.reverse = NULL,
by = NULL,
vars.to.factor = NULL,
iqr = "auto",
prevalence = FALSE,
percent = c("column", "row", "none"),
frequency = TRUE,
test = TRUE,
name.test = TRUE,
total.column = FALSE,
simulate.p.value = FALSE,
sample.size = TRUE,
assumption.p.value = 0.01,
NAcol = FALSE,
NArow = FALSE,
drplvls = FALSE
)
Arguments
vars
a vector of variables in the data frame. The imput may be given with or without quotes.
dataFrame
source data frame of the variables
minlevel
possible minimum value of items specified by user
maxlevel
possible maximum value of items specified by user
count
whether number of valid records for each item will be displayed
na.rm
whether missing value would be removed during calculation mean score of each person
means
whether means of all selected items will be displayed
medians
whether medians of all selected items will be displayed
sds
whether standard deviations of all selected items will be displayed
decimal
number of decimals displayed
total
display of means and standard deviations of total and average scores
var.labels
presence of descriptions of variables on the last column of output
var.labels.trunc
number of characters used for variable description
reverse
whether item(s) negatively correlated with other majority will be reversed
vars.to.reverse
variable(s) to reverse
by
a variable for column breakdown. If NONE is given, only the 'total column' will be displayed. More on Details.
vars.to.factor
variable(s) to be converted to factor for tabulaton
iqr
variable(s) to display median and inter-quartile range
prevalence
for logical or dichotomous variables, whether prevalence of the dichotomous row variable in each column subgroup will be displayed
percent
type of percentage displayed when the variable is categorical and for NArow when activated. Default is column
frequency
whether to display frequency in the cells when the variable is categorical and for NArow when activated
test
whether statistical test(s) will be computed
name.test
display name of the test and relevant degrees of freedom
total.column
whether to add 'total column' to the output or not
simulate.p.value
simulate P value for Fisher's exact test
sample.size
whether to display non-missing sample size of each column
assumption.p.value
level of Bartlett's test P value to judge whether the comparison and the test should be parametric
NAcol
whether to add 'NA column' to the output or not
NArow
whether to add 'NA rows' for each variable to the output or not
drplvls
whether to hide non used levels on factor and character variables or not
Details
This function is a clone of tableStack from the epiDisplay package. Comparing to the original, tt adds options to show the NA in the variables as categories, similar to the option useNA in the table function, and it also fix few bugs, such as showing the total.column without the need to test = TRUE, and to show or hide levels with zero counts without returning error.
This function simultaneously explores several variables with a fixed integer rating scale. For non-factor variables, the default values for tabulation are the minimum and the maximum of all variables but can be specified by the user.
When 'by' is omitted, all variables must be of the same class, and must be 'integer', 'factor' or 'logical. Some parameters are only used if by is omitted, others are only used if by is available. The by-omitted dependent variable are minlevel, maxlevel, count, na.rm, means, medians, sds, total, reverse, vars.to.reverse. The by-available dependent variables are iqr, prevalence, percent, frequency, test, name.test, total.column, simulate.p.value, sample.size, assumption.p.value, NArow, NAcol, drplvls.
Unlike function 'alpha', the argument 'reverse' has a default value of FALSE. This argument is ignored if 'vars.to.reverse' is specified.
Options for 'reverse', 'vars.to.reverse' and statistics of 'means', 'medians', 'sds' and 'total' are available only if the items are not factor. To obtain statistics of factor items, users need to use 'unclassDataframe' to convert them into integer.
When the 'by' argument is given, 'reverse' and 'vars.to.reverse' do not apply, as mentioned before. Instead, columns of the 'by' variable will be formed. A table will be created against each selected variable. If the variable is a factor or coerced to factor with 'vars.to.factor', cross-tabulation will result with percents as specified, ie. "column", "row", or "none" (FALSE). For a dichotomous row variable, if set to 'TRUE', the prevalence of row variable in the form of a fraction is displayed in each subgroup column. For objects of class 'numeric' or 'integer', means with standard deviations will be displayed. For variables with residuals that are not normally distributed or where the variance of subgroups are significantly not normally distributed (using a significance level of 0.01), medians and inter-quartile ranges will be presented if the argument 'iqr' is set to "auto" (by default). Users may specify a subset of the selected variables (from the 'vars' argument) to be presented in such a form. Otherwise, the argument could be set as any other character string, except the variables names, to insist to present means and standard deviations.
When 'test = TRUE' (default), Pearson's chi-squared test (or a two-sided Fisher's exact test, if the sample size is small) will be carried out for a categorical variable or a factor. Parametric or non-parametric comparison and test will be carried out for a object of class 'numeric' or 'integer' (See 'iqr' and 'assumption.p.value' below). If the sample size of the numeric variable is too small in any group, the test is omitted and the problem reported.
For Fisher's exact test, the default method employs 'simulate.p.value = FALSE'. See further explanation in 'fisher.test' procedure. If the dataset is extraordinarily large, the option may be manually set to TRUE.
When 'by' is specified as a single character object (such as 'by="none"') or when 'by = NONE' there will be no column breakdown and all tests will be omitted. Only the total column is displayed. Only the 'total' column is shown.
If this 'total column' is to accompany the 'by' breakdown, the argument 'total.column=TRUE' should be specified. The 'sample.size' is TRUE by default. The total number of records for each group is displayed in the first row of the output. However, the variable in each row may have some missing records, the information on which is reported by NArow for each variable on 'vars' and by NAcol for the variable on 'by'.
By default, Epicalc sets 'var.labels=TRUE' in order to give nice output. However, 'var.labels=FALSE' can sometimes be more useful during data exploration. Variable numbers as well as variable names are displayed instead of variable labels. Names and numbers of abnormally distributed variables, especially factors with too many levels, can be easily identified for further relevelling or recoding.
The argument 'iqr' has a default value being "auto". Non-parametric comparison and test will be automatically chosen if Bartlett's test P value is below the 'assumption.p.value'.
The test can be forced to parametric by setting 'iqr=NULL' and to non-parametric by if iqr is set to the variable number of cont.var (See examples.).
Value
an object of class 'tableStack' and 'list' when by=NULL
results an object of class 'noquote' which is used for print out
items.reversed name(s) of variable(s) reversed
total.score a vector from 'rowSums' of the columns of variables specified in 'vars'
mean.score a vector from 'rowMeans' of the columns of variables specified in 'vars'
mean.of.total.scores mean of total scores
sd.of.total.scores standard deviation of total scores
mean.of.average.scores mean of mean scores
sd.of.average.scores standard deviation of mean scores
When 'by' is specified, an object of class 'tableStack' and 'table is returned.
Author(s)
Virasakdi Chongsuvivatwong <cvirasak@medicine.psu.ac.th>
Caio Ferreira <caio.ferreira@epimedsolutions.com>
Lunna Borges <caio.ferreira@epimedsolutions.com>
Pedro Brasil <pedro.brasil@epimedsolutions.com>
References
'table', 'tab1', 'summ', 'alpha', 'unclassDataframe'
Examples
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
set.seed(1)
data <- data.frame(sex = sample(c("M","F"), 50, rep = TRUE),
age = sample(c(NA,20:70), 50, rep = TRUE),
admissionType = sample(c(NA,"urgency", "clinical", "scheduled"), 50, rep = TRUE),
hospitalizationTime = sample(c(0:10), 50, rep = TRUE),
numberOfChildren = sample(c(NA,0:3), 50, rep = TRUE),
cancerInFamily = sample(c(NA,TRUE,FALSE), 50, rep = TRUE),
diabetesInFamily = sample(c(TRUE,FALSE), 50, rep = TRUE),
thrombosisInFamily = sample(c(TRUE,FALSE), 50, rep = TRUE),
mentaldiseasesInFamily = sample(c(TRUE,FALSE), 50, rep = TRUE),
cardiadicdiseaseInFamily = sample(c(NA,TRUE,FALSE), 50, rep = TRUE),
readmission = sample(c(NA,TRUE,FALSE), 50, rep = TRUE))
attach(data)
tableStack(cancerInFamily:cardiadicdiseaseInFamily, dataFrame = data)
detach(data)
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data) # Default data frame is data
# "by" compares variables
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data, by= readmission)
# "prevalence" returns the prevalence instead of the absolute values
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data,
by= readmission, prevalence=TRUE)
# "percent" as FALSE hides the percentage in parenthesis
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data,
by= readmission, percent=FALSE)
# "name.test" as FALSE hides the column that shows the tests names
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data,
by= readmission, percent=FALSE, name.test=FALSE)
# "NAcol" displays a column of NA values on the variable on "by"
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data,
by= readmission, NAcol = TRUE)
# "NArow" displays rows of NA values on the variables on "vars"
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data,
by= readmission, NAcol = TRUE, NArow = TRUE)
# the specification of the vars may be done as the range
tableStack(vars=2:7, data, by=sex)
# "by" var may be specified as "none" and the selected vars will be crossed only against the total
tableStack(vars=2:7, data, by="none")
# by = NONE works just as by = "none"
tableStack(vars=2:7, data, by = NONE)
# total.column displays a column of totals in adition to the variable on by
tableStack(vars=2:7, data, by=sex, total.column=TRUE)
var.labels <- c("sex", "Type of admission for each patient",
"age", "Duration time in days of the patient's hospitalization",
"Number of children that the patient have",
"whether or not the patient has cancer in family",
"whether or not the patient has diabetes in family",
"whether or not the patient has thrombosis in family",
"whether or not the patient has mental diseases in family",
"whether or not the patient has cardiac diseases in family",
"whether or not the patient is on a relapse admission")
#setting the attribute var.labels
attr(data, "var.labels") <- var.labels
rm(var.labels)
# May need full screen of Rconsole
tableStack(vars=c(numberOfChildren,hospitalizationTime), data)
# Fits in with default R console screen
tableStack(vars=c(numberOfChildren,hospitalizationTime), data,
var.labels.trunc=35)
tableStack(vars=c(age,numberOfChildren,hospitalizationTime),
data, reverse=TRUE) -> a
a
## Components of 'a' have appropriate items reversed
a$mean.score -> mean.score
a$total.score -> total.score
data$mean.score <- mean.score
data$total.score <- total.score
# hiding the test column
tableStack(c(age, numberOfChildren,hospitalizationTime,
mean.score,total.score), data, by=sex, test=FALSE)
# variables specified on iqr will not display SD but IQR instead
tableStack(3:5, data, by=sex, iqr=hospitalizationTime)
## 'vars' can be mixture of variables of different classes
tableStack(3:5, data, by=admissionType,
iqr=c(hospitalizationTime, total.score))
data$highscore <- mean.score > 4
# a variable with some comparison may be created easily
tableStack(mean.score:highscore, data,
by=sex, iqr=total.score)
# the percentage information may be hidden
tableStack(vars=c(readmission,admissionType),
data, by=sex, percent="none")
# it may be shown the prevalende of the
# variable instead of the values themselves
tableStack(vars=c(readmission,admissionType), data,
by=sex, prevalence = TRUE)
# the name of the tests may be hidden
# while the test itself still shows
tableStack(vars=c(readmission,admissionType), data,
by=sex, name.test = FALSE)
## Variable in numeric or factor
# as continuous varaibles
tableStack(vars=3:5, data, by=sex)
# as factors
tableStack(vars=3:5, data, by=sex, vars.to.factor = 3:5)
## Using drplvls
# a dataframe will be created containing a factor with an unused level
bloodbank <- data.frame(AgeInDays =
sample(0:15,200, replace = TRUE), Type =
factor(sample(c("A","B","0"), 200, replace = TRUE),
levels = c("A","B","AB","0")), Origin =
sample(c("US","CA"), 200, replace = TRUE))
# by using drplvls the row of the unused fator is hidden
tableStack(vars = c(AgeInDays, Type),
bloodbank, by = Origin) #usual
tableStack(vars = c(AgeInDays, Type),
bloodbank, by = Origin,
drplvls = TRUE) # with drplvls
rm(total.score, mean.score, a, data, bloodbank)
Example output
$results
FALSE TRUE count mean sd
cancerInFamily 16 15 31 0.48 0.51
diabetesInFamily 21 29 50 0.58 0.50
thrombosisInFamily 25 25 50 0.50 0.51
mentaldiseasesInFamily 16 34 50 0.68 0.47
cardiadicdiseaseInFamily 8 19 27 0.70 0.47
Total score 18 2.44 1.20
Average score 18 0.49 0.24
attr(,"class")
[1] "tableStack" "list"
$results
FALSE TRUE count mean sd
cancerInFamily 16 15 31 0.48 0.51
diabetesInFamily 21 29 50 0.58 0.50
thrombosisInFamily 25 25 50 0.50 0.51
mentaldiseasesInFamily 16 34 50 0.68 0.47
cardiadicdiseaseInFamily 8 19 27 0.70 0.47
Total score 18 2.44 1.20
Average score 18 0.49 0.24
attr(,"class")
[1] "tableStack" "list"
FALSE TRUE Test stat. P.Value
Total 18 19
cancerInFamily Fisher's exact test 0.6882
FALSE 7 (43.75) 5 (55.56)
TRUE 9 (56.25) 4 (44.44)
diabetesInFamily Chisq. (1 df) = 0.029 0.8658
FALSE 8 (44.44) 10 (52.63)
TRUE 10 (55.56) 9 (47.37)
thrombosisInFamily Chisq. (1 df) = 0.029 0.8658
FALSE 10 (55.56) 9 (47.37)
TRUE 8 (44.44) 10 (52.63)
mentaldiseasesInFamily Chisq. (1 df) = 0.015 0.9037
FALSE 7 (38.89) 6 (31.58)
TRUE 11 (61.11) 13 (68.42)
cardiadicdiseaseInFamily Fisher's exact test 0.6424
No 4 (36.36) 2 (22.22)
Yes 7 (63.64) 7 (77.78)
FALSE TRUE
Total 18 19
cancerInFamily
prevalence 9/16 (56.25%) 4/9 (44.44%)
diabetesInFamily
prevalence 10/18 (55.56%) 9/19 (47.37%)
thrombosisInFamily
prevalence 8/18 (44.44%) 10/19 (52.63%)
mentaldiseasesInFamily
prevalence 11/18 (61.11%) 13/19 (68.42%)
cardiadicdiseaseInFamily = Yes
prevalence 7/11 (63.64%) 7/9 (77.78%)
Test stat. P.Value
Total
cancerInFamily Fisher's exact test 0.6882
prevalence
diabetesInFamily Chisq. (1 df) = 0.029 0.8658
prevalence
thrombosisInFamily Chisq. (1 df) = 0.029 0.8658
prevalence
mentaldiseasesInFamily Chisq. (1 df) = 0.015 0.9037
prevalence
cardiadicdiseaseInFamily = Yes Fisher's exact test 0.6424
prevalence
FALSE TRUE Test stat. P.Value
Total 18 19
cancerInFamily Fisher's exact test 0.6882
FALSE 7 5
TRUE 9 4
diabetesInFamily Chisq. (1 df) = 0.029 0.8658
FALSE 8 10
TRUE 10 9
thrombosisInFamily Chisq. (1 df) = 0.029 0.8658
FALSE 10 9
TRUE 8 10
mentaldiseasesInFamily Chisq. (1 df) = 0.015 0.9037
FALSE 7 6
TRUE 11 13
cardiadicdiseaseInFamily Fisher's exact test 0.6424
No 4 2
Yes 7 7
FALSE TRUE P.Value
Total 18 19
cancerInFamily 0.6882
FALSE 7 5
TRUE 9 4
diabetesInFamily 0.8658
FALSE 8 10
TRUE 10 9
thrombosisInFamily 0.8658
FALSE 10 9
TRUE 8 10
mentaldiseasesInFamily 0.9037
FALSE 7 6
TRUE 11 13
cardiadicdiseaseInFamily 0.6424
No 4 2
Yes 7 7
FALSE TRUE NA Test stat.
Total 18 19 13
cancerInFamily Fisher's exact test
FALSE 7 (43.75) 5 (55.56) 4 (66.67)
TRUE 9 (56.25) 4 (44.44) 2 (33.33)
diabetesInFamily Chisq. (1 df) = 0.029
FALSE 8 (44.44) 10 (52.63) 3 (23.08)
TRUE 10 (55.56) 9 (47.37) 10 (76.92)
thrombosisInFamily Chisq. (1 df) = 0.029
FALSE 10 (55.56) 9 (47.37) 6 (46.15)
TRUE 8 (44.44) 10 (52.63) 7 (53.85)
mentaldiseasesInFamily Chisq. (1 df) = 0.015
FALSE 7 (38.89) 6 (31.58) 3 (23.08)
TRUE 11 (61.11) 13 (68.42) 10 (76.92)
cardiadicdiseaseInFamily Fisher's exact test
No 4 (36.36) 2 (22.22) 2 (28.57)
Yes 7 (63.64) 7 (77.78) 5 (71.43)
P.Value
Total
cancerInFamily 0.6882
FALSE
TRUE
diabetesInFamily 0.8658
FALSE
TRUE
thrombosisInFamily 0.8658
FALSE
TRUE
mentaldiseasesInFamily 0.9037
FALSE
TRUE
cardiadicdiseaseInFamily 0.6424
No
Yes
FALSE TRUE NA Test stat.
Total 18 19 13
cancerInFamily Chisq. (1 df) = 0.023
FALSE 7 (38.89) 5 (26.32) 4 (30.77)
TRUE 9 (50.00) 4 (21.05) 2 (15.38)
NA 2 (11.11) 10 (52.63) 7 (53.85)
diabetesInFamily Fisher's exact test
FALSE 8 (44.44) 10 (52.63) 3 (23.08)
TRUE 10 (55.56) 9 (47.37) 10 (76.92)
NA 0 (0.00) 0 (0.00) 0 (0.00)
thrombosisInFamily Fisher's exact test
FALSE 10 (55.56) 9 (47.37) 6 (46.15)
TRUE 8 (44.44) 10 (52.63) 7 (53.85)
NA 0 (0.00) 0 (0.00) 0 (0.00)
mentaldiseasesInFamily Fisher's exact test
FALSE 7 (38.89) 6 (31.58) 3 (23.08)
TRUE 11 (61.11) 13 (68.42) 10 (76.92)
NA 0 (0.00) 0 (0.00) 0 (0.00)
cardiadicdiseaseInFamily Chisq. (1 df) = 0.038
No 4 (22.22) 2 (10.53) 2 (15.38)
Yes 7 (38.89) 7 (36.84) 5 (38.46)
NA 7 (38.89) 10 (52.63) 6 (46.15)
P.Value
Total
cancerInFamily 0.8807
FALSE
TRUE
NA
diabetesInFamily 0.7459
FALSE
TRUE
NA
thrombosisInFamily 0.7459
FALSE
TRUE
NA
mentaldiseasesInFamily 0.7374
FALSE
TRUE
NA
cardiadicdiseaseInFamily 0.8445
No
Yes
NA
F M
Total 23 27
age
mean (SD) 44.68 (12.16) 48.96 (16.11)
admissionType
clinical 7 (36.84) 9 (42.86)
scheduled 5 (26.32) 5 (23.81)
urgency 7 (36.84) 7 (33.33)
hospitalizationTime
median (IQR) 4.00 (1.00 - 6.50) 3.00 (2.00 - 7.50)
numberOfChildren
median (IQR) 2.00 (0.00 - 3.00) 2.00 (1.75 - 3.00)
cancerInFamily
FALSE 8 (57.14) 8 (47.06)
TRUE 6 (42.86) 9 (52.94)
diabetesInFamily
No 9 (39.13) 12 (44.44)
Yes 14 (60.87) 15 (55.56)
Test stat. P.Value
Total
age t-test (47 df) = 1.030 0.3084
mean (SD)
admissionType Chisq. (2 df) = 0.150 0.9276
clinical
scheduled
urgency
hospitalizationTime Ranksum test 0.4386
median (IQR)
numberOfChildren Ranksum test 0.2969
median (IQR)
cancerInFamily Chisq. (1 df) = 0.039 0.8430
FALSE
TRUE
diabetesInFamily Chisq. (1 df) = 0.008 0.9267
No
Yes
Total
Total 50
age
mean (SD) 47.04 (14.49)
admissionType
clinical 16 (40.00)
scheduled 10 (25.00)
urgency 14 (35.00)
hospitalizationTime
mean (SD) 4.26 (3.20)
numberOfChildren
mean (SD) 1.86 (1.16)
cancerInFamily
FALSE 16 (51.61)
TRUE 15 (48.39)
diabetesInFamily
No 21 (42.00)
Yes 29 (58.00)
Total
Total 50
age
mean (SD) 47.04 (14.49)
admissionType
clinical 16 (40.00)
scheduled 10 (25.00)
urgency 14 (35.00)
hospitalizationTime
mean (SD) 4.26 (3.20)
numberOfChildren
mean (SD) 1.86 (1.16)
cancerInFamily
FALSE 16 (51.61)
TRUE 15 (48.39)
diabetesInFamily
No 21 (42.00)
Yes 29 (58.00)
F M Total
Total 23 27 50
age
mean (SD) 44.68 (12.16) 48.96 (16.11) 47.04 (14.49)
admissionType
clinical 7 (36.84) 9 (42.86) 16 (40.00)
scheduled 5 (26.32) 5 (23.81) 10 (25.00)
urgency 7 (36.84) 7 (33.33) 14 (35.00)
hospitalizationTime
median (IQR) 4.00 (1.00 - 6.50) 3.00 (2.00 - 7.50) 3.50 (2.00 - 7.00)
numberOfChildren
median (IQR) 2.00 (0.00 - 3.00) 2.00 (1.75 - 3.00) 2.00 (1.00 - 3.00)
cancerInFamily
FALSE 8 (57.14) 8 (47.06) 16 (51.61)
TRUE 6 (42.86) 9 (52.94) 15 (48.39)
diabetesInFamily
No 9 (39.13) 12 (44.44) 21 (42.00)
Yes 14 (60.87) 15 (55.56) 29 (58.00)
Test stat. P.Value
Total
age t-test (47 df) = 1.030 0.3084
mean (SD)
admissionType Chisq. (2 df) = 0.150 0.9276
clinical
scheduled
urgency
hospitalizationTime Ranksum test 0.4386
median (IQR)
numberOfChildren Ranksum test 0.2969
median (IQR)
cancerInFamily Chisq. (1 df) = 0.039 0.8430
FALSE
TRUE
diabetesInFamily Chisq. (1 df) = 0.008 0.9267
No
Yes
$results
0 1 2 3 4 5 6 7 8 9 10 count mean sd
numberOfChildren 8 3 12 14 0 0 0 0 0 0 0 37 1.86 1.16
hospitalizationTime 5 7 10 3 2 4 4 4 5 3 3 50 4.26 3.20
Total score 37 6.05 3.61
Average score 37 3.03 1.81
description
numberOfChildren Number of children that the patient have
hospitalizationTime Duration time in days of the patient's hospitalization
Total score
Average score
$item.labels
[1] "Number of children that the patient have"
[2] "Duration time in days of the patient's hospitalization"
$total.score
[1] 5 7 6 NA 7 3 5 7 4 8 2 NA 1 NA NA 9 8 NA 2 8 13 8 NA NA 10
[26] 5 NA 5 5 1 0 NA 11 12 9 4 1 4 0 4 13 4 4 NA 10 9 NA NA 10 NA
$mean.score
[1] 2.5 3.5 3.0 NA 3.5 1.5 2.5 3.5 2.0 4.0 1.0 NA 0.5 NA NA 4.5 4.0 NA 1.0
[20] 4.0 6.5 4.0 NA NA 5.0 2.5 NA 2.5 2.5 0.5 0.0 NA 5.5 6.0 4.5 2.0 0.5 2.0
[39] 0.0 2.0 6.5 2.0 2.0 NA 5.0 4.5 NA NA 5.0 NA
$mean.of.total.scores
[1] 6.054054
$sd.of.total.scores
[1] 3.612832
$mean.of.average.scores
[1] 3.027027
$sd.of.average.scores
[1] 1.806416
attr(,"class")
[1] "tableStack" "list"
$results
0 1 2 3 4 5 6 7 8 9 10 count mean sd
numberOfChildren 8 3 12 14 0 0 0 0 0 0 0 37 1.86 1.16
hospitalizationTime 5 7 10 3 2 4 4 4 5 3 3 50 4.26 3.20
Total score 37 6.05 3.61
Average score 37 3.03 1.81
description
numberOfChildren Number of children that the patient
hospitalizationTime Duration time in days of the patien
Total score
Average score
$item.labels
[1] "Number of children that the patient have"
[2] "Duration time in days of the patient's hospitalization"
$total.score
[1] 5 7 6 NA 7 3 5 7 4 8 2 NA 1 NA NA 9 8 NA 2 8 13 8 NA NA 10
[26] 5 NA 5 5 1 0 NA 11 12 9 4 1 4 0 4 13 4 4 NA 10 9 NA NA 10 NA
$mean.score
[1] 2.5 3.5 3.0 NA 3.5 1.5 2.5 3.5 2.0 4.0 1.0 NA 0.5 NA NA 4.5 4.0 NA 1.0
[20] 4.0 6.5 4.0 NA NA 5.0 2.5 NA 2.5 2.5 0.5 0.0 NA 5.5 6.0 4.5 2.0 0.5 2.0
[39] 0.0 2.0 6.5 2.0 2.0 NA 5.0 4.5 NA NA 5.0 NA
$mean.of.total.scores
[1] 6.054054
$sd.of.total.scores
[1] 3.612832
$mean.of.average.scores
[1] 3.027027
$sd.of.average.scores
[1] 1.806416
attr(,"class")
[1] "tableStack" "list"
$results
Reversed 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
age . 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
numberOfChildren . 8 3 12 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
hospitalizationTime . 5 7 10 3 2 4 4 4 5 3 3 0 0 0 0 0 0 0 0
Total score
Average score
19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38
age 0 1 0 0 0 5 0 0 0 0 1 0 2 2 0 0 1 1 0 1
numberOfChildren 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
hospitalizationTime 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Total score
Average score
39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58
age 1 2 2 1 3 0 0 1 2 0 0 1 1 0 0 1 0 1 3 4
numberOfChildren 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
hospitalizationTime 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Total score
Average score
59 60 61 62 63 64 65 66 67 68 69 count mean sd
age 0 1 0 3 2 1 0 2 0 0 3 49 47.04 14.49
numberOfChildren 0 0 0 0 0 0 0 0 0 0 0 37 1.86 1.16
hospitalizationTime 0 0 0 0 0 0 0 0 0 0 0 50 4.26 3.20
Total score 36 53.89 16.72
Average score 36 17.96 5.57
description
age Type of admission for each patient
numberOfChildren Number of children that the patient have
hospitalizationTime Duration time in days of the patient's hospitalization
Total score
Average score
$items.reversed
character(0)
$item.labels
[1] "Type of admission for each patient"
[2] "Number of children that the patient have"
[3] "Duration time in days of the patient's hospitalization"
$total.score
[1] 29 65 68 NA 31 60 74 67 28 50 52 NA 21 NA NA 49 40 NA NA 77 82 66 NA NA 72
[26] 29 NA 62 34 36 54 NA 69 55 75 47 42 68 38 61 60 35 44 NA 56 71 NA NA 73 NA
$mean.score
[1] 9.666667 21.666667 22.666667 NA 10.333333 20.000000 24.666667
[8] 22.333333 9.333333 16.666667 17.333333 NA 7.000000 NA
[15] NA 16.333333 13.333333 NA NA 25.666667 27.333333
[22] 22.000000 NA NA 24.000000 9.666667 NA 20.666667
[29] 11.333333 12.000000 18.000000 NA 23.000000 18.333333 25.000000
[36] 15.666667 14.000000 22.666667 12.666667 20.333333 20.000000 11.666667
[43] 14.666667 NA 18.666667 23.666667 NA NA 24.333333
[50] NA
$mean.of.total.scores
[1] 53.88889
$sd.of.total.scores
[1] 16.72257
$mean.of.average.scores
[1] 17.96296
$sd.of.average.scores
[1] 5.574191
attr(,"class")
[1] "tableStack" "list"
F
Total 23
Type of admission for each patient
mean (SD) 44.68 (12.16)
Number of children that the patient have
median (IQR) 2.00 (0.00 - 3.00)
Duration time in days of the patient's hospitalization
median (IQR) 4.00 (1.00 - 6.50)
<NA>
mean (SD) 16.06 (4.29)
<NA>
mean (SD) 48.19 (12.87)
M
Total 27
Type of admission for each patient
mean (SD) 48.96 (16.11)
Number of children that the patient have
median (IQR) 2.00 (1.75 - 3.00)
Duration time in days of the patient's hospitalization
median (IQR) 3.00 (2.00 - 7.50)
<NA>
mean (SD) 19.48 (6.10)
<NA>
mean (SD) 58.45 (18.30)
F
Total 23
age
clinical 7 (36.84)
scheduled 5 (26.32)
urgency 7 (36.84)
Duration time in days of the patient's hospitalization
median (IQR) 4.00 (1.00 - 6.50)
Number of children that the patient have
mean (SD) 1.65 (1.22)
M
Total 27
age
clinical 9 (42.86)
scheduled 5 (23.81)
urgency 7 (33.33)
Duration time in days of the patient's hospitalization
median (IQR) 3.00 (2.00 - 7.50)
Number of children that the patient have
mean (SD) 2.05 (1.10)
Test stat.
Total
age Chisq. (2 df) = 0.150
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization Ranksum test
median (IQR)
Number of children that the patient have t-test (35 df) = 1.056
mean (SD)
P.Value
Total
age 0.9276
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization 0.4386
median (IQR)
Number of children that the patient have 0.2982
mean (SD)
clinical
Total 16
age
clinical 16 (100.00)
scheduled 0 (0.00)
urgency 0 (0.00)
Duration time in days of the patient's hospitalization
median (IQR) 2.00 (1.75 - 5.25)
Number of children that the patient have
mean (SD) 2.33 (1.15)
scheduled
Total 10
age
clinical 0 (0.00)
scheduled 10 (100.00)
urgency 0 (0.00)
Duration time in days of the patient's hospitalization
median (IQR) 2.00 (1.00 - 5.75)
Number of children that the patient have
mean (SD) 1.40 (1.17)
urgency
Total 14
age
clinical 0 (0.00)
scheduled 0 (0.00)
urgency 14 (100.00)
Duration time in days of the patient's hospitalization
median (IQR) 5.50 (3.25 - 6.75)
Number of children that the patient have
mean (SD) 1.88 (0.83)
Test stat.
Total
age Fisher's exact test
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization Kruskal-Wallis test
median (IQR)
Number of children that the patient have ANOVA F-test (2, 27 df) = 2.011
mean (SD)
P.Value
Total
age < 0.001
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization 0.0877
median (IQR)
Number of children that the patient have 0.1534
mean (SD)
F M
Total 23 27
<NA>
mean (SD) 16.06 (4.29) 19.48 (6.10)
<NA>
median (IQR) 49.50 (37.50 - 57.00) 66.50 (46.25 - 72.25)
<NA>
No 16 (100.00) 20 (100.00)
Yes 0 (0.00) 0 (0.00)
Test stat. P.Value
Total
<NA> t-test (34 df) = 1.896 0.0664
mean (SD)
<NA> Ranksum test 0.0416
median (IQR)
<NA> Fisher's exact test 1.0000
No
Yes
F M
Total 23 27
whether or not the patient is on a relapse admission
FALSE 8 10
TRUE 9 10
age
clinical 7 9
scheduled 5 5
urgency 7 7
Test stat.
Total
whether or not the patient is on a relapse admission Chisq. (1 df) = 0.000
FALSE
TRUE
age Chisq. (2 df) = 0.150
clinical
scheduled
urgency
P.Value
Total
whether or not the patient is on a relapse admission 1.0000
FALSE
TRUE
age 0.9276
clinical
scheduled
urgency
F
Total 23
whether or not the patient is on a relapse admission
prevalence 9/17 (52.94%)
age
clinical 7 (36.84)
scheduled 5 (26.32)
urgency 7 (36.84)
M
Total 27
whether or not the patient is on a relapse admission
prevalence 10/20 (50.00%)
age
clinical 9 (42.86)
scheduled 5 (23.81)
urgency 7 (33.33)
Test stat.
Total
whether or not the patient is on a relapse admission Chisq. (1 df) = 0.000
prevalence
age Chisq. (2 df) = 0.150
clinical
scheduled
urgency
P.Value
Total
whether or not the patient is on a relapse admission 1.0000
prevalence
age 0.9276
clinical
scheduled
urgency
F M
Total 23 27
whether or not the patient is on a relapse admission
FALSE 8 (47.06) 10 (50.00)
TRUE 9 (52.94) 10 (50.00)
age
clinical 7 (36.84) 9 (42.86)
scheduled 5 (26.32) 5 (23.81)
urgency 7 (36.84) 7 (33.33)
P.Value
Total
whether or not the patient is on a relapse admission 1.0000
FALSE
TRUE
age 0.9276
clinical
scheduled
urgency
F
Total 23
age
clinical 7 (36.84)
scheduled 5 (26.32)
urgency 7 (36.84)
Duration time in days of the patient's hospitalization
median (IQR) 4.00 (1.00 - 6.50)
Number of children that the patient have
median (IQR) 2.00 (0.00 - 3.00)
M
Total 27
age
clinical 9 (42.86)
scheduled 5 (23.81)
urgency 7 (33.33)
Duration time in days of the patient's hospitalization
median (IQR) 3.00 (2.00 - 7.50)
Number of children that the patient have
median (IQR) 2.00 (1.75 - 3.00)
Test stat.
Total
age Chisq. (2 df) = 0.150
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization Ranksum test
median (IQR)
Number of children that the patient have Ranksum test
median (IQR)
P.Value
Total
age 0.9276
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization 0.4386
median (IQR)
Number of children that the patient have 0.2969
median (IQR)
F M
Total 23 27
age
clinical 7 (36.84) 9 (42.86)
scheduled 5 (26.32) 5 (23.81)
urgency 7 (36.84) 7 (33.33)
Duration time in days of the patient's hospitalization
0 3 (13.04) 2 (7.41)
1 5 (21.74) 2 (7.41)
2 3 (13.04) 7 (25.93)
3 0 (0.00) 3 (11.11)
4 2 (8.70) 0 (0.00)
5 2 (8.70) 2 (7.41)
6 2 (8.70) 2 (7.41)
7 2 (8.70) 2 (7.41)
8 1 (4.35) 4 (14.81)
9 1 (4.35) 2 (7.41)
10 2 (8.70) 1 (3.70)
Number of children that the patient have
0 5 (29.41) 3 (15.00)
1 1 (5.88) 2 (10.00)
2 6 (35.29) 6 (30.00)
3 5 (29.41) 9 (45.00)
Test stat.
Total
age Chisq. (2 df) = 0.150
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization Fisher's exact test
0
1
2
3
4
5
6
7
8
9
10
Number of children that the patient have Fisher's exact test
0
1
2
3
P.Value
Total
age 0.9276
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization 0.4740
0
1
2
3
4
5
6
7
8
9
10
Number of children that the patient have 0.6418
0
1
2
3
CA US Test stat.
Total 102 98
AgeInDays Ranksum test
median (IQR) 8.00 (4.00 - 11.00) 5.00 (3.00 - 12.00)
Type Fisher's exact test
A 37 (36.27) 31 (31.63)
B 38 (37.25) 38 (38.78)
AB 0 (0.00) 0 (0.00)
0 27 (26.47) 29 (29.59)
P.Value
Total
AgeInDays 0.2567
median (IQR)
Type 0.7797
A
B
AB
0
CA US Test stat.
Total 102 98
AgeInDays Ranksum test
median (IQR) 8.00 (4.00 - 11.00) 5.00 (3.00 - 12.00)
Type Chisq. (2 df) = 0.521
A 37 (36.27) 31 (31.63)
B 38 (37.25) 38 (38.78)
0 27 (26.47) 29 (29.59)
P.Value
Total
AgeInDays 0.2567
median (IQR)
Type 0.7706
A
B
0
ems documentation built on Dec. 11, 2021, 9:15 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Details Value Author(s) References Examples
Description
There are two functionalities: Tabulation of variables with the same possible range of distribution and stack into a new table with or without other descriptive statistics or to breakdown distribution of more than one row variables against a column variable
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | tableStack(
vars,
dataFrame,
minlevel = "auto",
maxlevel = "auto",
count = TRUE,
na.rm = FALSE,
means = TRUE,
medians = FALSE,
sds = TRUE,
decimal = 2,
total = TRUE,
var.labels = TRUE,
var.labels.trunc = 150,
reverse = FALSE,
vars.to.reverse = NULL,
by = NULL,
vars.to.factor = NULL,
iqr = "auto",
prevalence = FALSE,
percent = c("column", "row", "none"),
frequency = TRUE,
test = TRUE,
name.test = TRUE,
total.column = FALSE,
simulate.p.value = FALSE,
sample.size = TRUE,
assumption.p.value = 0.01,
NAcol = FALSE,
NArow = FALSE,
drplvls = FALSE
)
|
Arguments
vars |
a vector of variables in the data frame. The imput may be given with or without quotes. |
dataFrame |
source data frame of the variables |
minlevel |
possible minimum value of items specified by user |
maxlevel |
possible maximum value of items specified by user |
count |
whether number of valid records for each item will be displayed |
na.rm |
whether missing value would be removed during calculation mean score of each person |
means |
whether means of all selected items will be displayed |
medians |
whether medians of all selected items will be displayed |
sds |
whether standard deviations of all selected items will be displayed |
decimal |
number of decimals displayed |
total |
display of means and standard deviations of total and average scores |
var.labels |
presence of descriptions of variables on the last column of output |
var.labels.trunc |
number of characters used for variable description |
reverse |
whether item(s) negatively correlated with other majority will be reversed |
vars.to.reverse |
variable(s) to reverse |
by |
a variable for column breakdown. If NONE is given, only the 'total column' will be displayed. More on Details. |
vars.to.factor |
variable(s) to be converted to factor for tabulaton |
iqr |
variable(s) to display median and inter-quartile range |
prevalence |
for logical or dichotomous variables, whether prevalence of the dichotomous row variable in each column subgroup will be displayed |
percent |
type of percentage displayed when the variable is categorical and for NArow when activated. Default is column |
frequency |
whether to display frequency in the cells when the variable is categorical and for NArow when activated |
test |
whether statistical test(s) will be computed |
name.test |
display name of the test and relevant degrees of freedom |
total.column |
whether to add 'total column' to the output or not |
simulate.p.value |
simulate P value for Fisher's exact test |
sample.size |
whether to display non-missing sample size of each column |
assumption.p.value |
level of Bartlett's test P value to judge whether the comparison and the test should be parametric |
NAcol |
whether to add 'NA column' to the output or not |
NArow |
whether to add 'NA rows' for each variable to the output or not |
drplvls |
whether to hide non used levels on factor and character variables or not |
Details
This function is a clone of tableStack from the epiDisplay package. Comparing to the original, tt adds options to show the NA in the variables as categories, similar to the option useNA in the table function, and it also fix few bugs, such as showing the total.column without the need to test = TRUE, and to show or hide levels with zero counts without returning error.
This function simultaneously explores several variables with a fixed integer rating scale. For non-factor variables, the default values for tabulation are the minimum and the maximum of all variables but can be specified by the user.
When 'by' is omitted, all variables must be of the same class, and must be 'integer', 'factor' or 'logical. Some parameters are only used if by is omitted, others are only used if by is available. The by-omitted dependent variable are minlevel, maxlevel, count, na.rm, means, medians, sds, total, reverse, vars.to.reverse. The by-available dependent variables are iqr, prevalence, percent, frequency, test, name.test, total.column, simulate.p.value, sample.size, assumption.p.value, NArow, NAcol, drplvls. Unlike function 'alpha', the argument 'reverse' has a default value of FALSE. This argument is ignored if 'vars.to.reverse' is specified.
Options for 'reverse', 'vars.to.reverse' and statistics of 'means', 'medians', 'sds' and 'total' are available only if the items are not factor. To obtain statistics of factor items, users need to use 'unclassDataframe' to convert them into integer.
When the 'by' argument is given, 'reverse' and 'vars.to.reverse' do not apply, as mentioned before. Instead, columns of the 'by' variable will be formed. A table will be created against each selected variable. If the variable is a factor or coerced to factor with 'vars.to.factor', cross-tabulation will result with percents as specified, ie. "column", "row", or "none" (FALSE). For a dichotomous row variable, if set to 'TRUE', the prevalence of row variable in the form of a fraction is displayed in each subgroup column. For objects of class 'numeric' or 'integer', means with standard deviations will be displayed. For variables with residuals that are not normally distributed or where the variance of subgroups are significantly not normally distributed (using a significance level of 0.01), medians and inter-quartile ranges will be presented if the argument 'iqr' is set to "auto" (by default). Users may specify a subset of the selected variables (from the 'vars' argument) to be presented in such a form. Otherwise, the argument could be set as any other character string, except the variables names, to insist to present means and standard deviations.
When 'test = TRUE' (default), Pearson's chi-squared test (or a two-sided Fisher's exact test, if the sample size is small) will be carried out for a categorical variable or a factor. Parametric or non-parametric comparison and test will be carried out for a object of class 'numeric' or 'integer' (See 'iqr' and 'assumption.p.value' below). If the sample size of the numeric variable is too small in any group, the test is omitted and the problem reported.
For Fisher's exact test, the default method employs 'simulate.p.value = FALSE'. See further explanation in 'fisher.test' procedure. If the dataset is extraordinarily large, the option may be manually set to TRUE.
When 'by' is specified as a single character object (such as 'by="none"') or when 'by = NONE' there will be no column breakdown and all tests will be omitted. Only the total column is displayed. Only the 'total' column is shown.
If this 'total column' is to accompany the 'by' breakdown, the argument 'total.column=TRUE' should be specified. The 'sample.size' is TRUE by default. The total number of records for each group is displayed in the first row of the output. However, the variable in each row may have some missing records, the information on which is reported by NArow for each variable on 'vars' and by NAcol for the variable on 'by'.
By default, Epicalc sets 'var.labels=TRUE' in order to give nice output. However, 'var.labels=FALSE' can sometimes be more useful during data exploration. Variable numbers as well as variable names are displayed instead of variable labels. Names and numbers of abnormally distributed variables, especially factors with too many levels, can be easily identified for further relevelling or recoding.
The argument 'iqr' has a default value being "auto". Non-parametric comparison and test will be automatically chosen if Bartlett's test P value is below the 'assumption.p.value'.
The test can be forced to parametric by setting 'iqr=NULL' and to non-parametric by if iqr is set to the variable number of cont.var (See examples.).
Value
an object of class 'tableStack' and 'list' when by=NULL
results | an object of class 'noquote' which is used for print out |
items.reversed | name(s) of variable(s) reversed |
total.score | a vector from 'rowSums' of the columns of variables specified in 'vars' |
mean.score | a vector from 'rowMeans' of the columns of variables specified in 'vars' |
mean.of.total.scores | mean of total scores |
sd.of.total.scores | standard deviation of total scores |
mean.of.average.scores | mean of mean scores |
sd.of.average.scores | standard deviation of mean scores |
When 'by' is specified, an object of class 'tableStack' and 'table is returned.
Author(s)
Virasakdi Chongsuvivatwong <cvirasak@medicine.psu.ac.th>
Caio Ferreira <caio.ferreira@epimedsolutions.com>
Lunna Borges <caio.ferreira@epimedsolutions.com>
Pedro Brasil <pedro.brasil@epimedsolutions.com>
References
'table', 'tab1', 'summ', 'alpha', 'unclassDataframe'
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 | set.seed(1)
data <- data.frame(sex = sample(c("M","F"), 50, rep = TRUE),
age = sample(c(NA,20:70), 50, rep = TRUE),
admissionType = sample(c(NA,"urgency", "clinical", "scheduled"), 50, rep = TRUE),
hospitalizationTime = sample(c(0:10), 50, rep = TRUE),
numberOfChildren = sample(c(NA,0:3), 50, rep = TRUE),
cancerInFamily = sample(c(NA,TRUE,FALSE), 50, rep = TRUE),
diabetesInFamily = sample(c(TRUE,FALSE), 50, rep = TRUE),
thrombosisInFamily = sample(c(TRUE,FALSE), 50, rep = TRUE),
mentaldiseasesInFamily = sample(c(TRUE,FALSE), 50, rep = TRUE),
cardiadicdiseaseInFamily = sample(c(NA,TRUE,FALSE), 50, rep = TRUE),
readmission = sample(c(NA,TRUE,FALSE), 50, rep = TRUE))
attach(data)
tableStack(cancerInFamily:cardiadicdiseaseInFamily, dataFrame = data)
detach(data)
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data) # Default data frame is data
# "by" compares variables
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data, by= readmission)
# "prevalence" returns the prevalence instead of the absolute values
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data,
by= readmission, prevalence=TRUE)
# "percent" as FALSE hides the percentage in parenthesis
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data,
by= readmission, percent=FALSE)
# "name.test" as FALSE hides the column that shows the tests names
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data,
by= readmission, percent=FALSE, name.test=FALSE)
# "NAcol" displays a column of NA values on the variable on "by"
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data,
by= readmission, NAcol = TRUE)
# "NArow" displays rows of NA values on the variables on "vars"
tableStack(cancerInFamily:cardiadicdiseaseInFamily, data,
by= readmission, NAcol = TRUE, NArow = TRUE)
# the specification of the vars may be done as the range
tableStack(vars=2:7, data, by=sex)
# "by" var may be specified as "none" and the selected vars will be crossed only against the total
tableStack(vars=2:7, data, by="none")
# by = NONE works just as by = "none"
tableStack(vars=2:7, data, by = NONE)
# total.column displays a column of totals in adition to the variable on by
tableStack(vars=2:7, data, by=sex, total.column=TRUE)
var.labels <- c("sex", "Type of admission for each patient",
"age", "Duration time in days of the patient's hospitalization",
"Number of children that the patient have",
"whether or not the patient has cancer in family",
"whether or not the patient has diabetes in family",
"whether or not the patient has thrombosis in family",
"whether or not the patient has mental diseases in family",
"whether or not the patient has cardiac diseases in family",
"whether or not the patient is on a relapse admission")
#setting the attribute var.labels
attr(data, "var.labels") <- var.labels
rm(var.labels)
# May need full screen of Rconsole
tableStack(vars=c(numberOfChildren,hospitalizationTime), data)
# Fits in with default R console screen
tableStack(vars=c(numberOfChildren,hospitalizationTime), data,
var.labels.trunc=35)
tableStack(vars=c(age,numberOfChildren,hospitalizationTime),
data, reverse=TRUE) -> a
a
## Components of 'a' have appropriate items reversed
a$mean.score -> mean.score
a$total.score -> total.score
data$mean.score <- mean.score
data$total.score <- total.score
# hiding the test column
tableStack(c(age, numberOfChildren,hospitalizationTime,
mean.score,total.score), data, by=sex, test=FALSE)
# variables specified on iqr will not display SD but IQR instead
tableStack(3:5, data, by=sex, iqr=hospitalizationTime)
## 'vars' can be mixture of variables of different classes
tableStack(3:5, data, by=admissionType,
iqr=c(hospitalizationTime, total.score))
data$highscore <- mean.score > 4
# a variable with some comparison may be created easily
tableStack(mean.score:highscore, data,
by=sex, iqr=total.score)
# the percentage information may be hidden
tableStack(vars=c(readmission,admissionType),
data, by=sex, percent="none")
# it may be shown the prevalende of the
# variable instead of the values themselves
tableStack(vars=c(readmission,admissionType), data,
by=sex, prevalence = TRUE)
# the name of the tests may be hidden
# while the test itself still shows
tableStack(vars=c(readmission,admissionType), data,
by=sex, name.test = FALSE)
## Variable in numeric or factor
# as continuous varaibles
tableStack(vars=3:5, data, by=sex)
# as factors
tableStack(vars=3:5, data, by=sex, vars.to.factor = 3:5)
## Using drplvls
# a dataframe will be created containing a factor with an unused level
bloodbank <- data.frame(AgeInDays =
sample(0:15,200, replace = TRUE), Type =
factor(sample(c("A","B","0"), 200, replace = TRUE),
levels = c("A","B","AB","0")), Origin =
sample(c("US","CA"), 200, replace = TRUE))
# by using drplvls the row of the unused fator is hidden
tableStack(vars = c(AgeInDays, Type),
bloodbank, by = Origin) #usual
tableStack(vars = c(AgeInDays, Type),
bloodbank, by = Origin,
drplvls = TRUE) # with drplvls
rm(total.score, mean.score, a, data, bloodbank)
|
Example output
$results
FALSE TRUE count mean sd
cancerInFamily 16 15 31 0.48 0.51
diabetesInFamily 21 29 50 0.58 0.50
thrombosisInFamily 25 25 50 0.50 0.51
mentaldiseasesInFamily 16 34 50 0.68 0.47
cardiadicdiseaseInFamily 8 19 27 0.70 0.47
Total score 18 2.44 1.20
Average score 18 0.49 0.24
attr(,"class")
[1] "tableStack" "list"
$results
FALSE TRUE count mean sd
cancerInFamily 16 15 31 0.48 0.51
diabetesInFamily 21 29 50 0.58 0.50
thrombosisInFamily 25 25 50 0.50 0.51
mentaldiseasesInFamily 16 34 50 0.68 0.47
cardiadicdiseaseInFamily 8 19 27 0.70 0.47
Total score 18 2.44 1.20
Average score 18 0.49 0.24
attr(,"class")
[1] "tableStack" "list"
FALSE TRUE Test stat. P.Value
Total 18 19
cancerInFamily Fisher's exact test 0.6882
FALSE 7 (43.75) 5 (55.56)
TRUE 9 (56.25) 4 (44.44)
diabetesInFamily Chisq. (1 df) = 0.029 0.8658
FALSE 8 (44.44) 10 (52.63)
TRUE 10 (55.56) 9 (47.37)
thrombosisInFamily Chisq. (1 df) = 0.029 0.8658
FALSE 10 (55.56) 9 (47.37)
TRUE 8 (44.44) 10 (52.63)
mentaldiseasesInFamily Chisq. (1 df) = 0.015 0.9037
FALSE 7 (38.89) 6 (31.58)
TRUE 11 (61.11) 13 (68.42)
cardiadicdiseaseInFamily Fisher's exact test 0.6424
No 4 (36.36) 2 (22.22)
Yes 7 (63.64) 7 (77.78)
FALSE TRUE
Total 18 19
cancerInFamily
prevalence 9/16 (56.25%) 4/9 (44.44%)
diabetesInFamily
prevalence 10/18 (55.56%) 9/19 (47.37%)
thrombosisInFamily
prevalence 8/18 (44.44%) 10/19 (52.63%)
mentaldiseasesInFamily
prevalence 11/18 (61.11%) 13/19 (68.42%)
cardiadicdiseaseInFamily = Yes
prevalence 7/11 (63.64%) 7/9 (77.78%)
Test stat. P.Value
Total
cancerInFamily Fisher's exact test 0.6882
prevalence
diabetesInFamily Chisq. (1 df) = 0.029 0.8658
prevalence
thrombosisInFamily Chisq. (1 df) = 0.029 0.8658
prevalence
mentaldiseasesInFamily Chisq. (1 df) = 0.015 0.9037
prevalence
cardiadicdiseaseInFamily = Yes Fisher's exact test 0.6424
prevalence
FALSE TRUE Test stat. P.Value
Total 18 19
cancerInFamily Fisher's exact test 0.6882
FALSE 7 5
TRUE 9 4
diabetesInFamily Chisq. (1 df) = 0.029 0.8658
FALSE 8 10
TRUE 10 9
thrombosisInFamily Chisq. (1 df) = 0.029 0.8658
FALSE 10 9
TRUE 8 10
mentaldiseasesInFamily Chisq. (1 df) = 0.015 0.9037
FALSE 7 6
TRUE 11 13
cardiadicdiseaseInFamily Fisher's exact test 0.6424
No 4 2
Yes 7 7
FALSE TRUE P.Value
Total 18 19
cancerInFamily 0.6882
FALSE 7 5
TRUE 9 4
diabetesInFamily 0.8658
FALSE 8 10
TRUE 10 9
thrombosisInFamily 0.8658
FALSE 10 9
TRUE 8 10
mentaldiseasesInFamily 0.9037
FALSE 7 6
TRUE 11 13
cardiadicdiseaseInFamily 0.6424
No 4 2
Yes 7 7
FALSE TRUE NA Test stat.
Total 18 19 13
cancerInFamily Fisher's exact test
FALSE 7 (43.75) 5 (55.56) 4 (66.67)
TRUE 9 (56.25) 4 (44.44) 2 (33.33)
diabetesInFamily Chisq. (1 df) = 0.029
FALSE 8 (44.44) 10 (52.63) 3 (23.08)
TRUE 10 (55.56) 9 (47.37) 10 (76.92)
thrombosisInFamily Chisq. (1 df) = 0.029
FALSE 10 (55.56) 9 (47.37) 6 (46.15)
TRUE 8 (44.44) 10 (52.63) 7 (53.85)
mentaldiseasesInFamily Chisq. (1 df) = 0.015
FALSE 7 (38.89) 6 (31.58) 3 (23.08)
TRUE 11 (61.11) 13 (68.42) 10 (76.92)
cardiadicdiseaseInFamily Fisher's exact test
No 4 (36.36) 2 (22.22) 2 (28.57)
Yes 7 (63.64) 7 (77.78) 5 (71.43)
P.Value
Total
cancerInFamily 0.6882
FALSE
TRUE
diabetesInFamily 0.8658
FALSE
TRUE
thrombosisInFamily 0.8658
FALSE
TRUE
mentaldiseasesInFamily 0.9037
FALSE
TRUE
cardiadicdiseaseInFamily 0.6424
No
Yes
FALSE TRUE NA Test stat.
Total 18 19 13
cancerInFamily Chisq. (1 df) = 0.023
FALSE 7 (38.89) 5 (26.32) 4 (30.77)
TRUE 9 (50.00) 4 (21.05) 2 (15.38)
NA 2 (11.11) 10 (52.63) 7 (53.85)
diabetesInFamily Fisher's exact test
FALSE 8 (44.44) 10 (52.63) 3 (23.08)
TRUE 10 (55.56) 9 (47.37) 10 (76.92)
NA 0 (0.00) 0 (0.00) 0 (0.00)
thrombosisInFamily Fisher's exact test
FALSE 10 (55.56) 9 (47.37) 6 (46.15)
TRUE 8 (44.44) 10 (52.63) 7 (53.85)
NA 0 (0.00) 0 (0.00) 0 (0.00)
mentaldiseasesInFamily Fisher's exact test
FALSE 7 (38.89) 6 (31.58) 3 (23.08)
TRUE 11 (61.11) 13 (68.42) 10 (76.92)
NA 0 (0.00) 0 (0.00) 0 (0.00)
cardiadicdiseaseInFamily Chisq. (1 df) = 0.038
No 4 (22.22) 2 (10.53) 2 (15.38)
Yes 7 (38.89) 7 (36.84) 5 (38.46)
NA 7 (38.89) 10 (52.63) 6 (46.15)
P.Value
Total
cancerInFamily 0.8807
FALSE
TRUE
NA
diabetesInFamily 0.7459
FALSE
TRUE
NA
thrombosisInFamily 0.7459
FALSE
TRUE
NA
mentaldiseasesInFamily 0.7374
FALSE
TRUE
NA
cardiadicdiseaseInFamily 0.8445
No
Yes
NA
F M
Total 23 27
age
mean (SD) 44.68 (12.16) 48.96 (16.11)
admissionType
clinical 7 (36.84) 9 (42.86)
scheduled 5 (26.32) 5 (23.81)
urgency 7 (36.84) 7 (33.33)
hospitalizationTime
median (IQR) 4.00 (1.00 - 6.50) 3.00 (2.00 - 7.50)
numberOfChildren
median (IQR) 2.00 (0.00 - 3.00) 2.00 (1.75 - 3.00)
cancerInFamily
FALSE 8 (57.14) 8 (47.06)
TRUE 6 (42.86) 9 (52.94)
diabetesInFamily
No 9 (39.13) 12 (44.44)
Yes 14 (60.87) 15 (55.56)
Test stat. P.Value
Total
age t-test (47 df) = 1.030 0.3084
mean (SD)
admissionType Chisq. (2 df) = 0.150 0.9276
clinical
scheduled
urgency
hospitalizationTime Ranksum test 0.4386
median (IQR)
numberOfChildren Ranksum test 0.2969
median (IQR)
cancerInFamily Chisq. (1 df) = 0.039 0.8430
FALSE
TRUE
diabetesInFamily Chisq. (1 df) = 0.008 0.9267
No
Yes
Total
Total 50
age
mean (SD) 47.04 (14.49)
admissionType
clinical 16 (40.00)
scheduled 10 (25.00)
urgency 14 (35.00)
hospitalizationTime
mean (SD) 4.26 (3.20)
numberOfChildren
mean (SD) 1.86 (1.16)
cancerInFamily
FALSE 16 (51.61)
TRUE 15 (48.39)
diabetesInFamily
No 21 (42.00)
Yes 29 (58.00)
Total
Total 50
age
mean (SD) 47.04 (14.49)
admissionType
clinical 16 (40.00)
scheduled 10 (25.00)
urgency 14 (35.00)
hospitalizationTime
mean (SD) 4.26 (3.20)
numberOfChildren
mean (SD) 1.86 (1.16)
cancerInFamily
FALSE 16 (51.61)
TRUE 15 (48.39)
diabetesInFamily
No 21 (42.00)
Yes 29 (58.00)
F M Total
Total 23 27 50
age
mean (SD) 44.68 (12.16) 48.96 (16.11) 47.04 (14.49)
admissionType
clinical 7 (36.84) 9 (42.86) 16 (40.00)
scheduled 5 (26.32) 5 (23.81) 10 (25.00)
urgency 7 (36.84) 7 (33.33) 14 (35.00)
hospitalizationTime
median (IQR) 4.00 (1.00 - 6.50) 3.00 (2.00 - 7.50) 3.50 (2.00 - 7.00)
numberOfChildren
median (IQR) 2.00 (0.00 - 3.00) 2.00 (1.75 - 3.00) 2.00 (1.00 - 3.00)
cancerInFamily
FALSE 8 (57.14) 8 (47.06) 16 (51.61)
TRUE 6 (42.86) 9 (52.94) 15 (48.39)
diabetesInFamily
No 9 (39.13) 12 (44.44) 21 (42.00)
Yes 14 (60.87) 15 (55.56) 29 (58.00)
Test stat. P.Value
Total
age t-test (47 df) = 1.030 0.3084
mean (SD)
admissionType Chisq. (2 df) = 0.150 0.9276
clinical
scheduled
urgency
hospitalizationTime Ranksum test 0.4386
median (IQR)
numberOfChildren Ranksum test 0.2969
median (IQR)
cancerInFamily Chisq. (1 df) = 0.039 0.8430
FALSE
TRUE
diabetesInFamily Chisq. (1 df) = 0.008 0.9267
No
Yes
$results
0 1 2 3 4 5 6 7 8 9 10 count mean sd
numberOfChildren 8 3 12 14 0 0 0 0 0 0 0 37 1.86 1.16
hospitalizationTime 5 7 10 3 2 4 4 4 5 3 3 50 4.26 3.20
Total score 37 6.05 3.61
Average score 37 3.03 1.81
description
numberOfChildren Number of children that the patient have
hospitalizationTime Duration time in days of the patient's hospitalization
Total score
Average score
$item.labels
[1] "Number of children that the patient have"
[2] "Duration time in days of the patient's hospitalization"
$total.score
[1] 5 7 6 NA 7 3 5 7 4 8 2 NA 1 NA NA 9 8 NA 2 8 13 8 NA NA 10
[26] 5 NA 5 5 1 0 NA 11 12 9 4 1 4 0 4 13 4 4 NA 10 9 NA NA 10 NA
$mean.score
[1] 2.5 3.5 3.0 NA 3.5 1.5 2.5 3.5 2.0 4.0 1.0 NA 0.5 NA NA 4.5 4.0 NA 1.0
[20] 4.0 6.5 4.0 NA NA 5.0 2.5 NA 2.5 2.5 0.5 0.0 NA 5.5 6.0 4.5 2.0 0.5 2.0
[39] 0.0 2.0 6.5 2.0 2.0 NA 5.0 4.5 NA NA 5.0 NA
$mean.of.total.scores
[1] 6.054054
$sd.of.total.scores
[1] 3.612832
$mean.of.average.scores
[1] 3.027027
$sd.of.average.scores
[1] 1.806416
attr(,"class")
[1] "tableStack" "list"
$results
0 1 2 3 4 5 6 7 8 9 10 count mean sd
numberOfChildren 8 3 12 14 0 0 0 0 0 0 0 37 1.86 1.16
hospitalizationTime 5 7 10 3 2 4 4 4 5 3 3 50 4.26 3.20
Total score 37 6.05 3.61
Average score 37 3.03 1.81
description
numberOfChildren Number of children that the patient
hospitalizationTime Duration time in days of the patien
Total score
Average score
$item.labels
[1] "Number of children that the patient have"
[2] "Duration time in days of the patient's hospitalization"
$total.score
[1] 5 7 6 NA 7 3 5 7 4 8 2 NA 1 NA NA 9 8 NA 2 8 13 8 NA NA 10
[26] 5 NA 5 5 1 0 NA 11 12 9 4 1 4 0 4 13 4 4 NA 10 9 NA NA 10 NA
$mean.score
[1] 2.5 3.5 3.0 NA 3.5 1.5 2.5 3.5 2.0 4.0 1.0 NA 0.5 NA NA 4.5 4.0 NA 1.0
[20] 4.0 6.5 4.0 NA NA 5.0 2.5 NA 2.5 2.5 0.5 0.0 NA 5.5 6.0 4.5 2.0 0.5 2.0
[39] 0.0 2.0 6.5 2.0 2.0 NA 5.0 4.5 NA NA 5.0 NA
$mean.of.total.scores
[1] 6.054054
$sd.of.total.scores
[1] 3.612832
$mean.of.average.scores
[1] 3.027027
$sd.of.average.scores
[1] 1.806416
attr(,"class")
[1] "tableStack" "list"
$results
Reversed 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
age . 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
numberOfChildren . 8 3 12 14 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
hospitalizationTime . 5 7 10 3 2 4 4 4 5 3 3 0 0 0 0 0 0 0 0
Total score
Average score
19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38
age 0 1 0 0 0 5 0 0 0 0 1 0 2 2 0 0 1 1 0 1
numberOfChildren 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
hospitalizationTime 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Total score
Average score
39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58
age 1 2 2 1 3 0 0 1 2 0 0 1 1 0 0 1 0 1 3 4
numberOfChildren 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
hospitalizationTime 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Total score
Average score
59 60 61 62 63 64 65 66 67 68 69 count mean sd
age 0 1 0 3 2 1 0 2 0 0 3 49 47.04 14.49
numberOfChildren 0 0 0 0 0 0 0 0 0 0 0 37 1.86 1.16
hospitalizationTime 0 0 0 0 0 0 0 0 0 0 0 50 4.26 3.20
Total score 36 53.89 16.72
Average score 36 17.96 5.57
description
age Type of admission for each patient
numberOfChildren Number of children that the patient have
hospitalizationTime Duration time in days of the patient's hospitalization
Total score
Average score
$items.reversed
character(0)
$item.labels
[1] "Type of admission for each patient"
[2] "Number of children that the patient have"
[3] "Duration time in days of the patient's hospitalization"
$total.score
[1] 29 65 68 NA 31 60 74 67 28 50 52 NA 21 NA NA 49 40 NA NA 77 82 66 NA NA 72
[26] 29 NA 62 34 36 54 NA 69 55 75 47 42 68 38 61 60 35 44 NA 56 71 NA NA 73 NA
$mean.score
[1] 9.666667 21.666667 22.666667 NA 10.333333 20.000000 24.666667
[8] 22.333333 9.333333 16.666667 17.333333 NA 7.000000 NA
[15] NA 16.333333 13.333333 NA NA 25.666667 27.333333
[22] 22.000000 NA NA 24.000000 9.666667 NA 20.666667
[29] 11.333333 12.000000 18.000000 NA 23.000000 18.333333 25.000000
[36] 15.666667 14.000000 22.666667 12.666667 20.333333 20.000000 11.666667
[43] 14.666667 NA 18.666667 23.666667 NA NA 24.333333
[50] NA
$mean.of.total.scores
[1] 53.88889
$sd.of.total.scores
[1] 16.72257
$mean.of.average.scores
[1] 17.96296
$sd.of.average.scores
[1] 5.574191
attr(,"class")
[1] "tableStack" "list"
F
Total 23
Type of admission for each patient
mean (SD) 44.68 (12.16)
Number of children that the patient have
median (IQR) 2.00 (0.00 - 3.00)
Duration time in days of the patient's hospitalization
median (IQR) 4.00 (1.00 - 6.50)
<NA>
mean (SD) 16.06 (4.29)
<NA>
mean (SD) 48.19 (12.87)
M
Total 27
Type of admission for each patient
mean (SD) 48.96 (16.11)
Number of children that the patient have
median (IQR) 2.00 (1.75 - 3.00)
Duration time in days of the patient's hospitalization
median (IQR) 3.00 (2.00 - 7.50)
<NA>
mean (SD) 19.48 (6.10)
<NA>
mean (SD) 58.45 (18.30)
F
Total 23
age
clinical 7 (36.84)
scheduled 5 (26.32)
urgency 7 (36.84)
Duration time in days of the patient's hospitalization
median (IQR) 4.00 (1.00 - 6.50)
Number of children that the patient have
mean (SD) 1.65 (1.22)
M
Total 27
age
clinical 9 (42.86)
scheduled 5 (23.81)
urgency 7 (33.33)
Duration time in days of the patient's hospitalization
median (IQR) 3.00 (2.00 - 7.50)
Number of children that the patient have
mean (SD) 2.05 (1.10)
Test stat.
Total
age Chisq. (2 df) = 0.150
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization Ranksum test
median (IQR)
Number of children that the patient have t-test (35 df) = 1.056
mean (SD)
P.Value
Total
age 0.9276
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization 0.4386
median (IQR)
Number of children that the patient have 0.2982
mean (SD)
clinical
Total 16
age
clinical 16 (100.00)
scheduled 0 (0.00)
urgency 0 (0.00)
Duration time in days of the patient's hospitalization
median (IQR) 2.00 (1.75 - 5.25)
Number of children that the patient have
mean (SD) 2.33 (1.15)
scheduled
Total 10
age
clinical 0 (0.00)
scheduled 10 (100.00)
urgency 0 (0.00)
Duration time in days of the patient's hospitalization
median (IQR) 2.00 (1.00 - 5.75)
Number of children that the patient have
mean (SD) 1.40 (1.17)
urgency
Total 14
age
clinical 0 (0.00)
scheduled 0 (0.00)
urgency 14 (100.00)
Duration time in days of the patient's hospitalization
median (IQR) 5.50 (3.25 - 6.75)
Number of children that the patient have
mean (SD) 1.88 (0.83)
Test stat.
Total
age Fisher's exact test
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization Kruskal-Wallis test
median (IQR)
Number of children that the patient have ANOVA F-test (2, 27 df) = 2.011
mean (SD)
P.Value
Total
age < 0.001
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization 0.0877
median (IQR)
Number of children that the patient have 0.1534
mean (SD)
F M
Total 23 27
<NA>
mean (SD) 16.06 (4.29) 19.48 (6.10)
<NA>
median (IQR) 49.50 (37.50 - 57.00) 66.50 (46.25 - 72.25)
<NA>
No 16 (100.00) 20 (100.00)
Yes 0 (0.00) 0 (0.00)
Test stat. P.Value
Total
<NA> t-test (34 df) = 1.896 0.0664
mean (SD)
<NA> Ranksum test 0.0416
median (IQR)
<NA> Fisher's exact test 1.0000
No
Yes
F M
Total 23 27
whether or not the patient is on a relapse admission
FALSE 8 10
TRUE 9 10
age
clinical 7 9
scheduled 5 5
urgency 7 7
Test stat.
Total
whether or not the patient is on a relapse admission Chisq. (1 df) = 0.000
FALSE
TRUE
age Chisq. (2 df) = 0.150
clinical
scheduled
urgency
P.Value
Total
whether or not the patient is on a relapse admission 1.0000
FALSE
TRUE
age 0.9276
clinical
scheduled
urgency
F
Total 23
whether or not the patient is on a relapse admission
prevalence 9/17 (52.94%)
age
clinical 7 (36.84)
scheduled 5 (26.32)
urgency 7 (36.84)
M
Total 27
whether or not the patient is on a relapse admission
prevalence 10/20 (50.00%)
age
clinical 9 (42.86)
scheduled 5 (23.81)
urgency 7 (33.33)
Test stat.
Total
whether or not the patient is on a relapse admission Chisq. (1 df) = 0.000
prevalence
age Chisq. (2 df) = 0.150
clinical
scheduled
urgency
P.Value
Total
whether or not the patient is on a relapse admission 1.0000
prevalence
age 0.9276
clinical
scheduled
urgency
F M
Total 23 27
whether or not the patient is on a relapse admission
FALSE 8 (47.06) 10 (50.00)
TRUE 9 (52.94) 10 (50.00)
age
clinical 7 (36.84) 9 (42.86)
scheduled 5 (26.32) 5 (23.81)
urgency 7 (36.84) 7 (33.33)
P.Value
Total
whether or not the patient is on a relapse admission 1.0000
FALSE
TRUE
age 0.9276
clinical
scheduled
urgency
F
Total 23
age
clinical 7 (36.84)
scheduled 5 (26.32)
urgency 7 (36.84)
Duration time in days of the patient's hospitalization
median (IQR) 4.00 (1.00 - 6.50)
Number of children that the patient have
median (IQR) 2.00 (0.00 - 3.00)
M
Total 27
age
clinical 9 (42.86)
scheduled 5 (23.81)
urgency 7 (33.33)
Duration time in days of the patient's hospitalization
median (IQR) 3.00 (2.00 - 7.50)
Number of children that the patient have
median (IQR) 2.00 (1.75 - 3.00)
Test stat.
Total
age Chisq. (2 df) = 0.150
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization Ranksum test
median (IQR)
Number of children that the patient have Ranksum test
median (IQR)
P.Value
Total
age 0.9276
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization 0.4386
median (IQR)
Number of children that the patient have 0.2969
median (IQR)
F M
Total 23 27
age
clinical 7 (36.84) 9 (42.86)
scheduled 5 (26.32) 5 (23.81)
urgency 7 (36.84) 7 (33.33)
Duration time in days of the patient's hospitalization
0 3 (13.04) 2 (7.41)
1 5 (21.74) 2 (7.41)
2 3 (13.04) 7 (25.93)
3 0 (0.00) 3 (11.11)
4 2 (8.70) 0 (0.00)
5 2 (8.70) 2 (7.41)
6 2 (8.70) 2 (7.41)
7 2 (8.70) 2 (7.41)
8 1 (4.35) 4 (14.81)
9 1 (4.35) 2 (7.41)
10 2 (8.70) 1 (3.70)
Number of children that the patient have
0 5 (29.41) 3 (15.00)
1 1 (5.88) 2 (10.00)
2 6 (35.29) 6 (30.00)
3 5 (29.41) 9 (45.00)
Test stat.
Total
age Chisq. (2 df) = 0.150
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization Fisher's exact test
0
1
2
3
4
5
6
7
8
9
10
Number of children that the patient have Fisher's exact test
0
1
2
3
P.Value
Total
age 0.9276
clinical
scheduled
urgency
Duration time in days of the patient's hospitalization 0.4740
0
1
2
3
4
5
6
7
8
9
10
Number of children that the patient have 0.6418
0
1
2
3
CA US Test stat.
Total 102 98
AgeInDays Ranksum test
median (IQR) 8.00 (4.00 - 11.00) 5.00 (3.00 - 12.00)
Type Fisher's exact test
A 37 (36.27) 31 (31.63)
B 38 (37.25) 38 (38.78)
AB 0 (0.00) 0 (0.00)
0 27 (26.47) 29 (29.59)
P.Value
Total
AgeInDays 0.2567
median (IQR)
Type 0.7797
A
B
AB
0
CA US Test stat.
Total 102 98
AgeInDays Ranksum test
median (IQR) 8.00 (4.00 - 11.00) 5.00 (3.00 - 12.00)
Type Chisq. (2 df) = 0.521
A 37 (36.27) 31 (31.63)
B 38 (37.25) 38 (38.78)
0 27 (26.47) 29 (29.59)
P.Value
Total
AgeInDays 0.2567
median (IQR)
Type 0.7706
A
B
0
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.