| Title: | Functions for Weighting Effects | 
| Version: | 0.1.2 | 
| Description: | Functions for determining the effect of data weights on the variance of survey data: users will load a data set which has a weights column, and the package will calculate the design effect (DEFF), weighting loss, root design effect (DEFT), effective sample size (ESS), and/or weighted margin of error. | 
| Imports: | stats | 
| Depends: | R (≥ 3.5) | 
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] | 
| Encoding: | UTF-8 | 
| LazyData: | true | 
| RoxygenNote: | 6.1.1 | 
| Suggests: | knitr, rmarkdown | 
| VignetteBuilder: | knitr | 
| NeedsCompilation: | no | 
| Packaged: | 2019-06-09 21:12:18 UTC; JOSHUA | 
| Author: | Joshua Miller [aut, cre] | 
| Maintainer: | Joshua Miller <joshlmiller@msn.com> | 
| Repository: | CRAN | 
| Date/Publication: | 2019-06-09 22:30:03 UTC | 
Calculate DEFF
Description
Calculates design effect (DEFF)
Usage
DEFF(x)
Arguments
| x | = weights vector (name of weights column) | 
Value
Design effect (DEFF)
References
Design effect (DEFF) due to weighting => n * (sum(x^2) / sum(x)^2)
Examples
DEFF(testweights$weights_column)
Calculate DEFT
Description
Calculates root design effect (DEFT)
Usage
DEFT(x)
Arguments
| x | = weights vector (name of weights column) | 
Value
Root design effect (DEFT)
References
Root design effect (DEFT) => square root of DEFF
Examples
DEFT(testweights$weights_column)
Calculate ESS
Description
Calculates effective sample size (ESS)
Usage
ESS(x)
Arguments
| x | = weights vector (name of weights column) | 
Value
Effective sample size (ESS)
References
Effective sample size (ESS) => sum(x)^2 / sum(x^2)
Examples
ESS(testweights$weights_column)
Calculate Full Statistics
Description
Calculates DEFF, weighting loss, DEFT, ESS, and MOE
Usage
FULL(p = 50, conf = 95, N, wtcol)
Arguments
| p | = percentage for which MOE is calculated (optional, default is p = 50) | 
| conf | = level of confidence (optional, default is conf = 95) | 
| N | = population size (optional, used for finite population correction) | 
| wtcol | = Weights vector (name of weights column) | 
Value
DEFF, weighting loss, DEFT, ESS, and MOE
Examples
FULL(N=3000, wtcol=testweights$weights_column)
Calculate MOE
Description
Calculates weighted margin of error (MOE)
Usage
MOE(p = 50, conf = 95, N, wtcol)
Arguments
| p | = percentage for which MOE is calculated (optional, default is p = 50) | 
| conf | = level of confidence (optional, default is conf = 95) | 
| N | = population size (optional, used for finite population correction) | 
| wtcol | = Weights vector (name of weights column) | 
Value
Weighted margin of error (MOE)
References
Weighted margin of error (MOE) => unweighted MOE * DEFT
Examples
MOE(N=3000, wtcol=testweights$weights_column)
Calculate weighting loss
Description
Calculates weighting loss
Usage
WTGLOSS(x)
Arguments
| x | = weights vector (name of weights column) | 
Value
Weighting loss
References
Weighting loss => DEFF-1
Examples
WTGLOSS(testweights$weights_column)
An example weights column for a data set of 80 cases
Description
An example weights column for a data set of 80 cases
Usage
testweights
Format
A data frame with 80 rows and 1 variable
- weights_column
- data weights 
Source
Example data generated by author