RLVWT is a 16-digit numeric variable proving the replicate weight for the Leave Module.
NOTE: One-hundred sixty sets of 16-digit person (RLVWT_1- RLVWT_160) level replicate weights are included in extracts where this selection is made.
Description
Replicate weights allow users to generate empirically derived standard errors for estimates they produce. In theory, the standard error of an estimate measures the variation that can be expected in the estimated value of a statistic across multiple samples drawn from a given population. Researchers can use replicate weights to construct an estimate of the true standard error when only sample data are available.
RLVWT is available for Leave Module respondents only. Selecting RLVWT adds 160 replicate weights to your data set (variables named RLVWT _1 through RLVWT _160). Please be aware that including these variables will make your data file quite large. The Census Bureau produced these replicate weights by using what is known as the Successive Difference Replication (SDR) method, which involves repeated implementations of the initial weighting algorithm.
To calculate standard errors for an estimate, users should generate 160 separate estimates using each of the 160 replicate weights RLVWT _1 through RLVWT_160. Along with the single full-sample estimate that can be generated using LVWT, this information can then be used to compute the standard error of the estimate using the following formula provided by the Census Bureau:
where Y is the characteristic of interest,
Once calculated, the standard error is useful for constructing confidence intervals and in hypothesis testing. Both SAS and Stata include procedures that are designed to use the replicate weights to produce estimates of means, proportions and regression coefficients with correctly-calculated standard errors.
Additional information about the methodology used by the Census Bureau to create replicate weights can be found in Chapter 14 of CPS Technical Paper 66, available here.
User Note: The successive difference replication approach (SDR) is different from other methods for creating replicate weights such as balanced repeated replication (BRR) and jackknife estimation.
Comparability
No information available.Universe
- ATUS Leave Module respondents.
Availability
- 2011, 2017-2018
