Foliensatz
Praxis-Teil
“Eyeballing” mit skim
library(psych)
library(tidyverse)
library(skimr)
## Alle Daten:
skim(data)
## Interventionsgruppe:
data %>%
filter(group == 0) %>%
skim()
## Kontrollgruppe:
data %>%
filter(group == 1) %>%
skim()
## Histogramm des primären Outcomes (PSS-Stress)
multi.hist(data %>% select(pss.0, pss.1, pss.2), ncol = 3)
Dropout-Analyse
## Gesamte Daten
with(data, {
c(sum(is.na(pss.0)),
sum(is.na(pss.1)),
sum(is.na(pss.2)))
}) -> na.all
na.all.p <- na.all/nrow(data)
## Interventionsgruppe
data %>%
filter(group == 1) %>%
with({
c(sum(is.na(pss.0)),
sum(is.na(pss.1)),
sum(is.na(pss.2)))
}) -> na.ig
na.ig.p <- na.ig/nrow(data %>% filter(group == 1))
## Kontrollgruppe
data %>%
filter(group == 0) %>%
with({
c(sum(is.na(pss.0)),
sum(is.na(pss.1)),
sum(is.na(pss.2)))
}) -> na.cg
na.cg.p <- na.cg/nrow(data %>% filter(group == 0))
## Sammeln in Dataframe
na <- data.frame(na.all, na.all.p = na.all.p*100,
na.ig, na.ig.p = na.ig.p*100,
na.cg, na.cg.p = na.cg.p*100)
## Zeilennamen des Dataframe ändern
rownames(na) = c("t0", "t1", "t2")
na