scd {survey} | R Documentation

## Survival in cardiac arrest

### Description

These data are from Section 12.2 of Levy and Lemeshow. They describe (a possibly apocryphal) study of survival in out-of-hospital cardiac arrest. Two out of five ambulance stations were sampled from each of three emergency service areas.

### Usage

    data(scd)

### Format

This data frame contains the following columns:

ESA
  Emergency Service Area (strata)
ambulance
  Ambulance station (PSU)
arrests
  estimated number of cardiac arrests
alive
  number reaching hospital alive

### Source

Levy and Lemeshow. "Sampling of Populations" (3rd edition). Wiley.

### Examples

    data(scd)

    ## survey design objects
    scddes<-svydesign(data=scd, prob=~1, id=~ambulance, strata=~ESA,
    nest=TRUE, fpc=rep(5,6))
    scdnofpc<-svydesign(data=scd, prob=~1, id=~ambulance, strata=~ESA,
    nest=TRUE)

    # convert to BRR replicate weights
    scd2brr <- as.svrepdesign(scdnofpc, type="BRR")

    # use BRR replicate weights from Levy and Lemeshow
    repweights<-2*cbind(c(1,0,1,0,1,0), c(1,0,0,1,0,1), c(0,1,1,0,0,1),
    c(0,1,0,1,1,0))
    scdrep<-svrepdesign(data=scd, type="BRR", repweights=repweights)

    # ratio estimates
    svyratio(~alive, ~arrests, design=scddes)
    svyratio(~alive, ~arrests, design=scdnofpc)
    svyratio(~alive, ~arrests, design=scd2brr)
    svyratio(~alive, ~arrests, design=scdrep)

    # or a logistic regression
    summary(svyglm(cbind(alive,arrests-alive)~1, family=quasibinomial, design=scdnofpc))
    summary(svyglm(cbind(alive,arrests-alive)~1, family=quasibinomial, design=scdrep))

    # Because no sampling weights are given, can't compute design effects
    # without replacement: use deff="replace"

    svymean(~alive+arrests, scddes, deff=TRUE)
    svymean(~alive+arrests, scddes, deff="replace")

[Package survey version 3.19 Index]