Description Usage Arguments Details Value See Also Examples

Calculate age-specific fertility rate (ASFR) and total fertility rate (TFR)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ```
calc_asfr(
data,
by = NULL,
agegr = 3:10 * 5,
period = NULL,
cohort = NULL,
tips = c(0, 3),
clusters = ~v021,
strata = ~v024 + v025,
id = "caseid",
dob = "v011",
intv = "v008",
weight = "v005",
varmethod = "lin",
bvars = grep("^b3\\_[0-9]*", names(data), value = TRUE),
birth_displace = 1e-06,
origin = 1900,
scale = 12,
bhdata = NULL,
counts = FALSE,
clustcounts = FALSE
)
``` |

`data` |
A dataset (data.frame), for example a DHS individual recode (IR) dataset. |

`by` |
A formula specifying factor variables by which to stratify analysis. |

`agegr` |
Numeric vector defining ages |

`period` |
Numeric vector defining calendar periods to stratify analysis, use |

`cohort` |
Numeric vector defining birth cohorts to stratify analysis, use |

`tips` |
Break points for TIme Preceding Survey. |

`clusters` |
Formula or data frame specifying cluster ids from largest level to smallest level, ‘~0’ or ‘~1’ is a formula for no clusters. |

`strata` |
Formula or vector specifying strata, use ‘NULL’ for no strata. |

`id` |
Variable name for identifying each individual respondent (character string). |

`dob` |
Variable name for date of birth of each individual (character string). |

`intv` |
Variable name for interview date (character string). |

`weight` |
Formula or vector specifying sampling weights. |

`varmethod` |
Method for variance calculation. Currently "lin" for Taylor linearisation or "jk1" for unstratified jackknife, or "jkn", for stratified jackknife. |

`bvars` |
Names of variables giving child dates of birth. If |

`birth_displace` |
Numeric value to displace multiple births date of birth by. Default is '1e-6'. |

`origin` |
Origin year for date arguments. 1900 for CMC inputs. |

`scale` |
Scale for dates inputs to calendar years. 12 for CMC inputs. |

`bhdata` |
A birth history dataset ( |

`counts` |
Whether to include counts of births & person-years ('pys')
in the returned |

`clustcounts` |
Whether to return additional attributes storing cluster
specific counts of births |

Events and person-years are calculated using normalized weights. Unweighted
aggregations may be output by specifying `weights=NULL`

(default) or
`weights=~1`

.

The assumption is that all dates in the data are specified in the same
format, typically century month code (CMC). The `period`

argument is
specified in calendar years (possibly non-integer).

Default values for `agegr`

, `period`

, and `tips`

parameters returns
age-specific fertility rates over the three-years preceding the survey,
the standard fertility indicator produced in DHS reports.

A `data.frame`

consisting of estimates and standard errors. The full
covariance matrix of the estimates can be retrieved by `vcov(val)`

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | ```
data(zzir)
## Replicate DHS Table 5.1
## ASFR and TFR in 3 years preceding survey by residence
calc_asfr(zzir, ~1, tips=c(0, 3))
reshape2::dcast(calc_asfr(zzir, ~v025, tips=c(0, 3)), agegr ~ v025, value.var = "asfr")
calc_tfr(zzir, ~v025)
calc_tfr(zzir, ~1)
## Replicate DHS Table 5.2
## TFR by resdience, region, education, and wealth quintile
calc_tfr(zzir, ~v102) # residence
calc_tfr(zzir, ~v101) # region
calc_tfr(zzir, ~v106) # education
calc_tfr(zzir, ~v190) # wealth
calc_tfr(zzir) # total
## Calculate annual TFR estimates for 10 years preceding survey
tfr_ann <- calc_tfr(zzir, tips=0:9)
## Sample covariance of annual TFR estimates arising from complex survey design
cov2cor(vcov(tfr_ann))
## Alternately, calculate TFR estimates by calendar year
tfr_cal <- calc_tfr(zzir, period = 2004:2015, tips=NULL)
tfr_cal
## sample covariance of annual TFR estimates arising from complex survey design
## Generate estimates split by period and TIPS
cov2cor(vcov(tfr_cal))
calc_tfr(zzir, period = c(2010, 2013, 2015), tips=0:5)
## ASFR estimates by birth cohort
asfr_coh <- calc_asfr(zzir, cohort=c(1980, 1985, 1990, 1995), tips=NULL)
reshape2::dcast(asfr_coh, agegr ~ cohort, value.var = "asfr")
``` |

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