deffH | R Documentation |

Compute the Henry design effect for single-stage samples when a general regression estimator is used for a total.

```
deffH(w, y, x)
```

`w` |
vector of inverses of selection probabilities for a sample |

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

`x` |
matrix of covariates used to construct a GREG estimator of the total of |

The Henry design effect is the ratio of the variance of the general regression (GREG) estimator of a total of `y`

to the variance of the estimated total in *srswr*. Calculations for the Henry *deff* are done as if the sample is selected in a single-stage and with replacement. Varying selection probabilities can be used. The model for the GREG is assumed to be `y = \alpha + \beta x + \epsilon`

, i.e., the model has an intercept.

numeric design effect

Richard Valliant, Jill A. Dever, Frauke Kreuter

Henry, K.A., and Valliant, R. (2015). A Design Effect Measure for Calibration Weighting in Single-stage Samples. *Survey Methodology*, 41, 315-331.

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

`deff`

, `deffCR`

, `deffK`

, `deffS`

```
set.seed(-500398777)
# generate population using HMT function
pop.dat <- as.data.frame(HMT())
mos <- pop.dat$x
pop.dat$prbs.1d <- mos / sum(mos)
# select pps sample
require(sampling)
n <- 80
pk <- n * pop.dat$prbs.1d
sam <- UPrandomsystematic(pk)
sam <- sam==1
sam.dat <- pop.dat[sam, ]
dsgn.wts <- 1/pk[sam]
deffH(w=dsgn.wts, y=sam.dat$y, x=sam.dat$x)
```

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.