neg2mis: Mark Negative Values as Missing

In memisc: Management of Survey Data and Presentation of Analysis Results

Mark Negative Values as Missing

Description

In many newer survey data sets available from social science data archives non-valid responses (such as "don't know" or "answer refused") are given negative codes. The function neg2miss allows to mark them as missing values.)

Usage

neg2mis(x,all=FALSE,exclude=NULL,select=NULL,zero=FALSE)

Arguments

x	an object that inherits from class "item.list", e.g. a "data.set" or an "importer" object.
all	logical; should the marking of negative values as missing applied to all variables?
exclude	an optional vector of variable naems to which the marking of negative values as missing should not be applied.
select	an optional vector of variable names to which the marking of negative values as missing should be applied.
zero	logical; should zeroes also be marked as missing?

Examples

ds <- data.set(
          var1 = c(0,1,-1,2,3),
          var2 = c(-1,-1,1,1,1),
          var3 = c(1,2,3,4,5)
          )
neg2mis(ds,all=TRUE)
neg2mis(ds,all=TRUE,zero=TRUE)
neg2mis(ds,exclude=var1)
neg2mis(ds,select=var1)

memisc documentation built on Oct. 24, 2024, 5:07 p.m.