miss_cell {etable} | R Documentation |
Missing values cell function
Description
Counting the number of missing values in each cell.
Usage
miss_cell(x, y, z, w, cell_ids, row_ids, col_ids, vnames, vars, n_min,
pct = FALSE, digits = 0, prefix='', suffix='')
Arguments
x |
The x variable |
y |
NOT USED |
z |
NOT USED |
w |
NOT USED (The number of missing will not be weighted!). |
cell_ids |
Index vector for selecting values in cell. |
row_ids |
NOT USED |
col_ids |
NOT USED |
vnames |
NOT USED |
vars |
NOT USED |
n_min |
NOT USED |
pct |
Logical asking whatever to draw absolute or relative frequency of missing values. |
digits |
Integer indicating the number of decimal places. |
prefix |
Free text added in each cell bevor results. |
suffix |
Free text added in each cell after results. |
Author(s)
Andreas Schulz <ades-s@web.de>
Examples
sex <- factor(rbinom(1000, 1, 0.4), labels=c('Men', 'Women'))
height <- rnorm(1000, mean=1.66, sd=0.1)
height[which(sex=='Men')]<-height[which(sex=='Men')]+0.1
weight <- rnorm(1000, mean=70, sd=5)
decades <- rbinom(1000, 3, 0.5)
decades <- factor(decades, labels=c('[35,45)','[45,55)','[55,65)','[65,75)'))
d<-data.frame(sex, decades, height, weight)
d$height[round(runif(250,1,1000))]<- NA
d$weight[round(runif(25 ,1,1000))]<- NA
tabular.ade(x_vars=c('height', 'weight'), xname=c('Height [m]','Weight [kg]'),
cols=c('sex','decades','ALL'), cnames=c('Gender', 'Age decades'),
data=d, FUN=miss_cell, prefix='Miss:')
[Package etable version 1.3.1 Index]