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Support #353

fed-forward (_ff_): what does this mean (doesn't always match previous wave)

Added by Phil Jones about 9 years ago. Updated about 9 years ago.

Status:
Closed
Priority:
Normal
Assignee:
Redmine Admin
Category:
Data inconsistency
Start date:
03/23/2015
% Done:

100%


Description

In wave 4 the fed-forward employment status (d_ff_jbstat) does not match the employment status provided in the previous wave (c_jbstat) in all cases.

I opened both c_indresp.tab and d_indresp.tab. I removed all variables except pidp (wave 4), pidp (wave 3), d_ff_jbstat, and c_jbstat. I merged these (on pidp) and tested to see if d_ff_jbstat and c_jbstat were equivalent.

In 456 cases they are not the same, although I assumed they would be.

R code below:

require("dplyr")
cind <- read.table("data/understandingSociety/UKDA-6614-tab/tab/c_indresp.tab",
                   header = T,
                   stringsAsFactors = F)
dind <- read.table("data/understandingSociety/UKDA-6614-tab/tab/d_indresp.tab",
                   header = T,
                   stringsAsFactors = F)
cindJbstat <- select(cind, pidp, c_jbstat)
dindJbstat <- select(dind, pidp, d_ff_jbstat)
dindJbstat <- inner_join(dindJbstat, cindJbstat)
# # joins on pidp
table(dindJbstat$d_ff_jbstat == dindJbstat$c_jbstat)
# FALSE  TRUE
# 456    39002

Have I misunderstood exactly what 'fed-forward' means, is this an error in the dataset, or is it the case that c_jbstat may have been incorrectly recorded in wave 3 and subsequently corrected in wave 4 by the interviewer, or something else entirely?

I've looked through the documentation to see if I can find an answer but haven't been able to, nor have I been able to find a similar open or closed issue.

Thank you.

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