missingness: Missing Analysis

In AnguloB/SubscaleExplorer: Psychometric scale explorer and management

Missing Analysis

Usage

missingness(df, group=NULL, pattern=FALSE,showNA=FALSE )

Arguments

df	dataframe or matrix
group	group (p.eg gender)
pattern	logical default FALSE. If true missing data pattern is printed
showNA	list with id of cases with completely missing data

Author(s)

Ariadna Angulo-Brunet ([e-mail]), Carme Viladrich

See Also

mice

Examples

x<-c(1:5, NA)
y<-1:2
v1<-sample(x,80,replace=TRUE)
v2<-sample(x,80,replace=TRUE)
v3<-sample(x,80,replace=TRUE)
v4<-sample(x,80,replace=TRUE)
gender<- sample(y, 80, replace=TRUE)
df <- data.frame(v1, v2,v3,v4)

missingness(df)

#by group
missingness(df, group=gender)

#by group with data pattern and completely missing data list
missingness(df, group=gender, pattern=TRUE, showNA=TRUE)

AnguloB/SubscaleExplorer documentation built on Feb. 23, 2025, 1:05 a.m.