deffCR | R Documentation |

Chen-Rust design effect for stratified, clustered, two-stage samples

deffCR(w, strvar=NULL, clvar=NULL, Wh=NULL, nest=FALSE, y)

`w` |
vector of weights for a sample |

`strvar` |
vector of stratum identifiers; equal in length to that of |

`clvar` |
vector of cluster identifiers; equal in length to that of |

`Wh` |
vector of the proportions of elements that are in each stratum; length is number of strata. |

`nest` |
Are cluster IDs numbered within strata ( |

`y` |
vector of the sample values of an analysis variable |

The Chen-Rust *deff* accounts for stratification, clustering, and unequal weights, but does not account for the use of any auxiliary data in the estimator of a mean. The Chen-Rust *deff* returned here is appropriate for stratified, two-stage sampling.

A list with components:

`strata components` |
Matrix with |

`overall deff` |
Design effect for full sample accounting for weighting, clustering, and stratification |

Richard Valliant, Jill A. Dever, Frauke Kreuter

Chen, S. and Rust, K. (2017). An Extension of Kish's Formula for Design Effects to Two- and Three-Stage Designs with Stratification. *Journal of Survey Statistics and Methodology*, 5(2), 111-130.

Valliant, R., Dever, J., Kreuter, F. (2018, chap. 14). *Practical Tools for Designing and Weighting Survey Samples, 2nd edition*. New York: Springer.

`deff`

, `deffH`

, `deffK`

, `deffS`

require(sampling) require(reshape) data(MDarea.pop) Ni <- table(MDarea.pop$TRACT) m <- 20 probi <- m*Ni / sum(Ni) # select sample of clusters set.seed(-780087528) sam <- sampling::cluster(data=MDarea.pop, clustername="TRACT", size=m, method="systematic", pik=probi, description=TRUE) # extract data for the sample clusters samclus <- getdata(MDarea.pop, sam) samclus <- rename(samclus, c(Prob = "pi1")) # treat sample clusters as strata and select srswor from each nbar <- 8 s <- sampling::strata(data = as.data.frame(samclus), stratanames = "TRACT", size = rep(nbar,m), method="srswor") # extracts the observed data samdat <- getdata(samclus,s) samdat <- rename(samdat, c(Prob = "pi2")) # add a fake stratum ID H <- 2 nh <- m * nbar / H stratum <- NULL for (h in 1:H){ stratum <- c(stratum, rep(h,nh)) } wt <- 1/(samdat$pi1*samdat$pi2) * runif(m*nbar) samdat <- cbind(subset(samdat, select = -c(Stratum)), stratum, wt) deffCR(w = samdat$wt, strvar = samdat$stratum, clvar = samdat$TRACT, Wh=NULL, y=samdat$y2)

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