APA_: APA Syle Table

In stp4/stp25stat: Functions for statistical computations

Description

APA_ICC:Intra-Klassen-Korrelation (mit psych).

APA_Ttest: Berechnung von Mittelwerten und Mittelwertdifferenzen und des T-Test.

APA_Correlation: Korrelationstabelle (Interkorrelationen mit der Hilfe der Funktion Hmisc::rcorr. Erlaubt ist die getrennte Auswertung ueber by=~b

Wird in APA2 verwendet Tabelle Arbeitet mit Multi2default() und hat anderen Rueckgabewert als Tabelle (Mittelverte vs String)

APA_PCA: Faktoranalyse wie SPSS PCA

APA_R2: R2-Tabelle (noch nicht fretig)

Kreuztabellen cross-tabulation, APA_Xtabs, APA2.xtabs : Die Funktion Formatiert xtabs() mit NxM und NxMxO Tabellen.

• "Haufigkeit/Prozent 1" Die Prozent werden ueber include.percent mit margin erstellt. Der Parameter add.margins wird automatisch vergeben. include.total, include.total.columns, include.total.sub, include.total.rows, include.percent, include.count. Feineinstellungen erfolgt ueber margin = 2).

• "Sensitivitaets Analyse"Nur bei 2x" Tabellen ueber test=TRUE

• "Sig.-Tests"Bei 2x" Tabellen Fischer sonst Chi-test. Die Berechnung erfolgt hier mit assocstats. Weiter Einstellungen sind Correlationen, Pearson, Kontingentkoeffizient berechnet alternativ steht auch der Phi-Coefficient

Usage

APA_ICC(
  ...,
  caption = "ICC",
  note = "",
  type = c(1, 4),
  output = which_output()
)

APA_Ttest(
  x,
  data,
  caption = "T Test",
  note = paste(type, alternative),
  output = stp25output::which_output(),
  var.equal = FALSE,
  paired = FALSE,
  alternative = "two.sided",
  include.mean = TRUE,
  include.d = TRUE,
  include.mean.diff = TRUE,
  include.se = FALSE,
  include.n = FALSE,
  type = "t.test",
  digits = 2,
  random = NULL,
  ...
)

APA_Correlation(
  ...,
  caption = "Korrelation",
  note = "",
  output = which_output(),
  col_names = NULL,
  cor_diagonale_up = TRUE,
  type = c("pearson", "spearman"),
  include.mean = FALSE,
  include.n = TRUE,
  stars = TRUE,
  p.value = FALSE,
  include.stars = stars,
  include.p = p.value
)

Hmisc_rcorr(
  ...,
  cor_diagonale_up = TRUE,
  include.stars = TRUE,
  include.p = FALSE,
  include.mean = FALSE,
  include.n = TRUE,
  type = c("pearson", "spearman"),
  caption = "",
  note = ""
)

APA_NULL(x, ...)

APA_Likert(...)

APA2_multiresponse(
  Formula,
  data,
  caption = "",
  note = "",
  test = FALSE,
  order = FALSE,
  decreasing = TRUE,
  sig_test = "fischer.test",
  na.action = na.pass,
  use.level = 1,
  output = which_output(),
  ...
)

APA_PCA(
  data,
  ...,
  include.pca = TRUE,
  include.loading = include.pca,
  include.test = include.pca,
  include.plot = FALSE,
  include.kmo = TRUE,
  w = 5,
  h = 5,
  opene_graphic_device = FALSE,
  save_graphic = opene_graphic_device,
  caption = "Standardized loadings (pattern matrix) based upon correlation matrix",
  note = "",
  output = which_output(),
  main = ""
)

APA_Reliability(..., caption = "", note = "", output = which_output())

APA_R2(..., caption, note)

APA_Xtabs(x, ...)

## S3 method for class 'glm'
APA_Xtabs(
  x,
  caption = "",
  output = stp25output::which_output(),
  thresh = 0.5,
  ...
)

## S3 method for class 'formula'
APA_Xtabs(
  x,
  data = NULL,
  caption = "",
  note = "",
  output = stp25output::which_output(),
  labels = TRUE,
  addNA = FALSE,
  exclude = if (!addNA) c(NA, NaN),
  drop.unused.levels = FALSE,
  ...
)

## S3 method for class 'xtabs'
APA_Xtabs(x, ...)

## Default S3 method:
APA_Xtabs(x, ...)

Arguments

...	extra arguments
caption, note	Ueberschrift an Output
type	enweder "pearson" oder "spearman"
output	Html oder Text
x	An object to be converted into a tidy data.frame or Formula
data	data.frame wenn x eine Formel ist
var.equal, paired, alternative	an t.Test var.equal = FALSE "two.sided"
include.mean	Mittelwerte
include.d	Cohens d
include.mean.diff	Mittlere Differenzen
include.se	Standardfehler noch nicht Fertig
include.n	Anzahl an gueltigen Werten
digits	Nachkommastellen
random	formula bei paired muss zwingend eine eindeutige id oder Fallnummer vorhanden sein
col_names	nicht benutzt
cor_diagonale_up	Diagonale oben oder unter
include.stars	Sternchen als p-Werte
include.p	Explizite p-Werte
Formula, test, order, decreasing, sig_test, na.action	Interne Parameter
include.pca, include.loading, include.test, include.plot, include.kmo	was soll ausgegeben werden
w, h, main, opene_graphic_device, save_graphic	Fenster w=5 h=5 Ueberschrift
addNA, exclude, drop.unused.levels	An xtabs() default = FALSE

Value

a data.frame or list with data.frame

Examples

 

 

APA_Ttest(m1+m2 ~ geschl, varana)
varanax<-Melt2(m1+m2~nr,varana , key="time", value="m")

# broom::tidy(with(varana, t.test(m1,m2 ) ))
# broom::tidy(  t.test(m~time, varanax, var.equal=FALSE)) )

APA_Ttest(m~time, varanax, paired = TRUE)



APA_Ttest(m~time, varanax, var.equal=TRUE)
APA_Ttest(m~time, varanax, var.equal=FALSE)
#broom::tidy(t.test(m~time, varanax, var.equal=TRUE))
#broom::tidy(t.test(m~time, varanax, var.equal=FALSE))

 varanax$m[1] <- NA
APA_Ttest(m ~ time, varanax, paired = TRUE, random=~nr, include.n=TRUE) 



n <- 2 * 20
e <- rnorm(n)
dat <- stp25aggregate::Label(
  data.frame(
    a = rnorm(n) + e / 2,
    b = rnorm(n) + e,
    c = rnorm(n),
    d = rnorm(n) + e * 10,
    g = gl(2, 20, labels = c("Control", "Treat"))
  ),
  a = "Alpha",
  b = "Beta",
  c = "Gamma"
)


APA_Correlation( ~ a + b + c, dat)
APA_Correlation(a ~ c, dat)
APA_Correlation(a + b + c ~ d, dat)
APA_Correlation(a + b ~ c +  d, dat)
APA_Correlation(a + b + c ~ d, dat, groups = ~ g)
APA_Correlation( ~ a + b + c, dat)
APA_Correlation( ~ a + b + c, dat, include.p = TRUE)
APA_Correlation( ~ a + b + c, dat, include.p = TRUE, include.stars = FALSE)

 # library(arm)
 # windows(7,7)
 # corrplot(data[Cs(a,b,c,d)], abs=TRUE, n.col.legend=7)

 # install.packages("PerformanceAnalytics")

 #library("PerformanceAnalytics")
 #?chart.Correlation#(decathlon2.active[, 1:6], histogram=TRUE, pch=19)
 #data(managers)
 #chart.Correlation(managers[,1:8], histogram=TRUE, pch="+")


fit1<-lm(score ~ grade + treatment, schools)
fit2<-lm(score ~ grade + treatment + stdTest, schools)
APA_R2(fit1, fit2)


 DF <- GetData(
"
GoldStandart Schnell.Test Anzahl
positiv positiv 124
positiv negativ 9
negativ positiv 20
negativ negativ 305 ",
Tabel_Expand = TRUE,
id.vars = 1:2,
output = FALSE
)



DF <- transform(
  DF,
  GoldStandart = factor(GoldStandart, rev(levels(DF$GoldStandart))),
  Schnell.Test = factor(Schnell.Test, rev(levels(DF$Schnell.Test)))
)

DF<- Label(DF, GoldStandart="Krank Covid-19", Schnell.Test= "Schnell Test GTV8")
N<- nrow(DF)


xtb <- xtabs( ~ Schnell.Test + GoldStandart  , DF)


APA_Xtabs(xtb)

APA_Xtabs( ~ Schnell.Test  + GoldStandart,
           DF,
           caption = "2x2 Tabelle zur Destimmung der Kennwerte",
           include.percent = FALSE,
           include.total=TRUE)

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