var_mvrg_cmpr

Run a standard error estimation for changes between time T0 and T1 in cross-sectional estimators using the multivariate regression approach for a proportional 0/1 indicator.

%var_mvrg_cmpr(idsn0=, yr0=, idsn1=, yr1=, odsn=, 
    cty_var=, strt=, clstr=, prp_ind=, ilib=WORK, olib=WORK);

Arguments

• idsn0 : the name of the input dataset at T0 in the work directory; it is the outdata_&odsn output dataset of the var_est_mvrg macro;
• yr0 : the year at time T0 for which the variance previously calculated by the var_est_mvrg macro;
• idsn1 : the name of the input dataset at T1 in the work directory; it is the outdata_&odsn output dataset of the var_est_mvrg macro;
• yr1 : the year at time T1 for which the variance previously calculated by the var_est_mvrg macro;
• cty_var : the name of the column in the input datasets which contains the country codes;
• strt : the name of the column in the input datasets which contains the starta information;
• clstr : the name of the column in the input datasets which contains the cluster/PSU information;
• prp_ind : the name of the column in the input datasets which contains the indicator variable which contains 0 or 1;
• ilib : (option) input library where both datasets idsn0 and idsn1 must be stored; default: ilib is set to WORK.

Returns

• odsn : name of the output dataset containig the country code, the indicator value at time T0, at time T1, and the standard error of the net change;
• olib : (option) output library; default: olib is set to WORK.

Example

Run for instance: ~~~sas var_mvrg_cmpr(idsn0=outdata_mvrgt0, yr0=2014, idsn1=outdata_mvrgt1, yr1=2015, odsn=arope_comparison, cty_var=DB020, strt=DB050, clstr=DB030, prp_ind=arope); ~~~

Note

The macro %var_mvrg_cmpr uses the implementation of variance estimation developed within the context of NET-SILC2 by [Osier et al, 2013] following the original algorithm of [Berger and Priam, 2010 and 2016].

References

1. Atkinson B., Guio A.-C. and Marlier E. eds (2017): "Monitoring social inclusion in Europe".
2. Berger, Y.G. and Priam, R. (2016): "A simple variance estimator of change for rotating repeated surveys: an application to the EU-SILC household surveys".
3. Osier G., Berger Y. and Goedeme T. (2013): "Standard error estimation for the EU–SILC indicators of poverty and social exclusion".
4. Berger Y. and Priam R. (2010): "Estimation of correlations between cross-sectional estimates from repeated surveys: an application to the variance of change".
5. Atkinson B. and Marlier E. eds (2010): "Income and living conditions in Europe".

See also

%var_est_mvrg, %var_est_srvyfrq.