wage1 | R Documentation |
A simulated dataset of office workers' salary (and associated information) in which workers exhibit multiple membership of companies worked for over past year.
wage1
A data frame with 3022 observations on the following 21 variables:
Unique office worker identifying code.
Identifying code for company worked for over the last 12 months.
If worked for >1 company over the last 12 months, identifying code for second company.
If worked for >2 companies over the last 12 months, identifying code for third company.
If worked for >3 companies over the last 12 months, identifying code for fourth company.
Age of worker.
Part or full-time, a factor with levels Fulltime
and
Parttime
.
Sex of worker, a factor with levels male
and
female
.
A column of ones. If included as an explanatory variable in a regression model (e.g. in MLwiN), its coefficient is the intercept.
Workers' earnings over the last financial year.
Workers' (natural) log-transformed earnings over the last financial year.
The number of companies worked for over the last 12 months.
Proportion of time worked for employer listed in
company
.
Proportion of time worked for employer listed in
company2
.
Proportion of time worked for employer listed in
company3
.
Proportion of time worked for employer listed in
company4
.
Alternative (equal) weighting for company
(1/numjobs
).
Alternative (equal) weighting for company2
(if numjobs >1
then 1/numjobs
, else 0).
Alternative (equal) weighting for company3
(if numjobs >2
then 1/numjobs
, else 0).
Alternative (equal) weighting for company4
(if numjobs >3
then 1/numjobs
,
else 0).
Age of worker, centered on 40 years.
The simulated wage1
dataset is one of the sample datasets provided
with the multilevel modelling software package MLwiN (Rasbash et al., 2009),
and described in Browne (2012). It consists of salary and associated
information for office workers, and is used by Browne (2012) as an example
of modelling a multiple membership structure. The dataset exhibits multiple
membership in that workers are clustered across the companies employing them
over the past year, but some have worked for more than one company during
that time.)
Browne, W. J. (2012) MCMC Estimation in MLwiN Version 2.26. University of Bristol: Centre for Multilevel Modelling.
Rasbash, J., Charlton, C., Browne, W.J., Healy, M. and Cameron, B. (2009) MLwiN Version 2.1. Centre for Multilevel Modelling, University of Bristol.
## Not run:
data(wage1, package = "R2MLwiN")
(mymodel <- runMLwiN(logearn ~ 1 + age_40 + numjobs + (1 | company) + (1 | id),
estoptions = list(EstM = 1,
mm = list(list(mmvar = list("company", "company2", "company3", "company4"),
weights = list("weight1", "weight2", "weight3", "weight4")), NA)),
data = wage1))
## End(Not run)
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