lavaan.survey (version 1.1.3)

ess4.gb: British attitudes towards the welfare state.

Description

European Social Survey (ESS) data from the 2008 (fourth) round in the United Kingdom. The data are from a questionnaire on "what the responsibilities of governments should or should not be". These were factor-analyzed by Roosma, Gelissen, and van Oorschot (2013). Also included are complex survey design variables.

Usage

data(ess4.gb)

Format

A data frame with 2273 observations of 13 variables.

idno

Respondent identifier.

psu

Primary sampling unit (PSU).

dweight

ESS design weights.

stratval

Stratification variable (UK regions).

gvjbevn

Job for everyone, governments' responsibility (0-10).

gvhlthc

Health care for the sick, governments' responsibility (0-10).

gvslvol

Standard of living for the old, governments' responsibility (0-10).

gvslvue

Standard of living for the unemployed, governments' responsibility (0-10).

gvcldcr

Child care services for working parents, governments' responsibility (0-10).

gvpdlwk

Paid leave from work to care for sick family, governments' responsibility (0-10).

sbprvpv

Social benefits/services prevent widespread poverty (1-5).

sbeqsoc

Social benefits/services lead to a more equal society (1-5).

sbcwkfm

Social benefits/services make it easier to combine work and family (1-5).

Source

This dataset was retrieved from http://www.europeansocialsurvey.org/data/download.html?r=4 and converted to an R dataset.

References

Jowell, R., Roberts, C., Fitzgerald, R., & Eva, G. (2007). Measuring attitudes cross-nationally: Lessons from the european social survey. SAGE.

Oberski, D.L. (2014). lavaan.survey: An R Package for Complex Survey Analysis of Structural Equation Models. Journal of Statistical Software, 57(1), 1-27. http://www.jstatsoft.org/v57/i01/.

Roosma F., Gelissen J., van Oorschot W. (2013). "The Multidimensionality of Welfare State Attitudes: A European Cross-National Study." Social Indicators Research, 113(1), 235-255.

See Also

lavaan.survey

Examples

  data(ess4.gb)
  
  # Two-factor model based on Roosma et al (2013).
  model.cfa <-    
    "range =~ gvjbevn + gvhlthc + gvslvol + gvslvue + gvcldcr + gvpdlwk
     goals =~ sbprvpv  +  sbeqsoc  +  sbcwkfm"
  
  # Fit the model using lavaan
  fit.cfa.ml <- lavaan(model.cfa, data = ess4.gb, estimator = "MLM",
    meanstructure = TRUE, int.ov.free = TRUE, auto.var = TRUE, 
    auto.fix.first = TRUE, auto.cov.lv.x = TRUE)
  fit.cfa.ml
  
  # Define the complex survey design for ESS 4 in the UK
  des.gb <- svydesign(ids = ~psu, strata = ~stratval, weights = ~dweight, 
    data = ess4.gb)
  
  # Fit the two-factor model while taking the survey design into account.
  fit.cfa.surv <- lavaan.survey(fit.cfa.ml, survey.design = des.gb)
  fit.cfa.surv