Tabelle: Tabelle

Description Usage Arguments Value Author(s) Examples

View source: R/Tabelle.R

Description

Einfache deskriptive Tabelle die in medizinischen Arbeiten verwendet werden. Die Funktion arbeitet Intern mit aggregate bzw. mit berechne_default() also aggregate(formula, data,FUN).

Tabelle2: html-Output Tabelle(...)

Describe2: workaraond fuer psych::describe()

Hilfsfunctionen Correlation in Dokument APA2_Correlation.R

conTest Hilfsfunktion fuer Tabellen

conTest Hilfsfunktion fuer Tabellen

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
 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
## S3 method for class 'lmerModLmerTest'
Tabelle(
  x,
  caption = NULL,
  note = "",
  digits = 2,
  fun = function(x) {     c(n = length(x), M = mean(x, na.rm = TRUE), SD = sd(x, na.rm
    = TRUE)) },
  ...
)

## S3 method for class 'glm'
Tabelle(
  x,
  caption = NULL,
  note = "",
  digits = 2,
  fun = function(x) {     f__n = length(x) },
  ...
)

## S3 method for class 'lm'
Tabelle(
  x,
  caption = NULL,
  note = "",
  digits = 2,
  fun = function(x) {     c(f__n = length(x), f__M = mean(x, na.rm = TRUE), f__SD =
    sd(x, na.rm = TRUE)) },
  ...
)

Tabelle(..., output = FALSE)

Tabelle2(..., output = which_output())

## S3 method for class ''NULL''
Tabelle()

## Default S3 method:
Tabelle(
  ...,
  formula = NULL,
  fun = NULL,
  type = c("2", "1", "freq", "freq.ci", "mean", "median", "ci", "cohen.d", "effsize",
    "multiresponse", "describe", "correlation", "custom_fun"),
  caption = "Charakteristik",
  note = "",
  digits = NULL,
  APA = FALSE,
  test = FALSE,
  na.action = na.pass,
  exclude = NA,
  include.n = TRUE,
  include.nr = FALSE,
  include.total = FALSE,
  include.test = test,
  exclude.level = NULL,
  max_factor_length = 35,
  order = FALSE,
  measure.name = "value"
)

Describe2(..., output = FALSE)

## S3 method for class 'data.frame'
Describe2(
  data,
  ...,
  by = NULL,
  caption = "",
  note = "",
  stat = c("n", "mean", "sd", "min", "max"),
  output = which_output(),
  digits = 2
)

## S3 method for class 'formula'
Describe2(
  x,
  data,
  by = NULL,
  caption = "",
  note = "",
  stat = c("n", "mean", "sd", "min", "max"),
  output = which_output(),
  digits = 2,
  ...
)

errate_statistik3(
  ...,
  type = NULL,
  caption = "",
  note = "",
  na.action = na.pass,
  exclude = NA,
  include.n = TRUE,
  include.nr = FALSE,
  include.total = FALSE,
  include.test = test,
  exclude.level = NULL,
  max_factor_length = 35,
  order = FALSE
)

conTest(fml, data, test_name = TRUE)

catTest(fml, data, include.test = "chisq.test")

Arguments

caption, note

Uberschrift an Output

digits

Kommastellen

fun

Eigene Function am Berechne

...

Die auszuwertenden Variablen sex, age="mean", usw

formula

An dcast Gruppe ~ .id ist zum Zeilen und Spalten vertauschen

type

1 oder 2 1 ist kurzes Format 2 int lang

APA

APA2 Style TRUE/FALSE

test, include.test

Signifikanz Test include.test "wilcox.test","u.test", "kruskal.test","h.test", "chisq.test","t.test", "aov", "anova", "SPSS", "Hmisc" "shapiro.test" "KS.test"

na.action, exclude

an Formula

include.n, include.nr, include.total

Anzahl ausgeben

exclude.level

Wenn ein Factor zwei Levels hat kann einer Ausgeschlossen werden exclude.level ="no" bei levels = c("yes", "no")

max_factor_length

Fehler bei langen Faktoren abfangen

stat

result von psych kann "n", "mean", "sd", "median", "trimmed", "mad", "min" , "max", "range", "skew", "kurtosis" ,"se"

Value

Tabelle: data.frame oder list mit data.frame Tabelle2: HTML

Author(s)

Wolfgang Peter

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
library(dplyr)
library(tidyr)
#names(varana)
#  set_my_options(mittelwert=list(median.style="Quantil")) # ++IQR
require(stp25data)
varana2 <- varana %>%
  gather(Zeit, Merkfgk, m1:m4) %>%
  mutate(Zeit = factor(Zeit, Cs(m1, m2, m3 , m4), Cs(t0, t1, t2, t3))) %>%
  stp25aggregate::Label(Merkfgk = "Merkfaehigkeit")

Tabelle(Merkfgk ~ Zeit, varana2)

varana2 %>% Tabelle(Merkfgk, by =  ~ Zeit)
varana %>% Tabelle(m1, m2, m3 , m4)


#varana %>% Tabelle(
#  4:7,
#  by =  ~ geschl,
#  fun = function(x)
#    c(
#      n = length(na.omit(x)),
#      m = mean(x),
#      sd = sd(x)
#   )
#)

 get_my_options()$apa.style$mittelwert$include_name

varana2 %>% Tabelle2(Merkfgk, by=~ Zeit)


 Tabelle(
m1[median] + m2[median] + m3[median] + m4[median] ~ geschl,
varana,
APA = TRUE,
include.n = FALSE,
test = TRUE
)

 c(
"wilcox"=Tabelle(alter ~ geschl, varana, APA=TRUE, test="wilcox")[[1]]$statistics[1],
"h.test"=Tabelle(alter ~ geschl, varana, APA=TRUE, test="h.test")[[1]]$statistics[1],
"anova"=Tabelle(alter ~ geschl, varana, APA=TRUE, test="anova")[[1]]$statistics[1],
"t.test"=Tabelle(alter ~ geschl, varana, APA=TRUE, test="t.test")[[1]]$statistics[1],
"hmisc"=Tabelle(alter ~ geschl, varana, APA=TRUE, test="Hmisc")[[1]]$statistics[1]
)


   Tabelle(alter ~ geschl, varana, APA=TRUE)

Tabelle(alter ~ geschl, varana, include.n=FALSE, APA=TRUE)
Tabelle(alter ~ geschl, varana, include.nr=TRUE, APA=TRUE)
Tabelle(alter ~ geschl, varana, include.total=TRUE, APA=TRUE)
Tabelle(alter ~ geschl, varana, include.test=TRUE, APA=TRUE)

stp4/stp25stat documentation built on Sept. 17, 2021, 2:03 p.m.