var_srs

Computes the estimation of the simple random sampling.

Variance

Generation of domain variables, linearization of several non-linear population statistics (the ratio of two totals, weighted income percentile, relative median income ratio, at-risk-of-poverty rate, at-risk-of-poverty threshold, Gini coefficient, gender pay gap, the aggregate replacement ratio, the relative median income ratio, median income below at-risk-of-poverty gap, income quintile share ratio, relative median at-risk-of-poverty gap), computation of regression residuals in case of weight calibration, variance estimation of sample surveys by the ultimate cluster method (Hansen, Hurwitz and Madow, Sample Survey Methods And Theory, vol. I: Methods and Applications; vol. II: Theory. 1953, New York: John Wiley and Sons), variance estimation for longitudinal, cross-sectional measures and measures of change for single and multistage stage cluster sampling designs (Berger, Y. G., 2015, <doi:10.1111/rssa.12116>). Several other precision measures are derived - standard error, the coefficient of variation, the margin of error, confidence interval, design effect.

Jelena Voronova

vardpoor

Variance Estimation for Sample Surveys by the Ultimate Cluster
Method

Juris Breidaks

Martins Liberts

Santa Ivanova

Aleksis Jursevskis

Anthony Damico

Liliana Roze

Central Statistical Bureau of Latvia 

var_srs function

<dl><dt>Y</dt>
<dd>The variables of interest.</dd>
<dt>w</dt>
<dd>Weight variable. One dimensional object convertible to one-column <code>data.frame</code>.</dd></dl>

Arguments

The estimation of the simple random sampling — var_srs

<dl>

<dt>Y</dt>
<dd>The variables of interest.</dd>


<dt>w</dt>
<dd>Weight variable. One dimensional object convertible to one-column <code>data.frame</code>.</dd>

</dl>

The estimation of the simple random sampling

var_srs: The estimation of the simple random sampling

Description

Usage

Value

Arguments

References

See Also

Examples