Sample size or precision for a rate

prec_rate returns the sample size or the precision for the provided rate.

prec_rate(
  r,
  x = NULL,
  conf.width = NULL,
  conf.level = 0.95,
  method = c("score", "vs", "exact", "wald"),
  ...
)

Arguments

r

rate or rate ratio.

x

number of events.

conf.width

precision (the full width of the confidence interval). Should not exceed 5 times r.

conf.level

confidence level.

method

The method to use to calculate precision. Exactly one method may be provided. Methods can be abbreviated.

...

other arguments to uniroot (e.g. tol).

Value

Object of class "presize", a list of arguments (including the computed one) augmented with method and note elements.

Details

Exactly one of the parameters r or conf.width must be passed as NULL, and that parameter is determined from the other.

The score, variance stabilizing (vs), exact, and wald method are implemented to calculate the rate and the precision. For few events x (<5), the exact method is recommended.

If more than one method is specified or the method is miss-specified, the 'score' method will be used.

uniroot is used to solve n for the score and exact method.

References

Barker, L. (2002) A Comparison of Nine Confidence Intervals for a Poisson Parameter When the Expected Number of Events is \(\le\) 5, The American Statistician, 56:2, 85-89, doi:10.1198/000313002317572736

See also

poisson.test

Examples

# confidence interval width for a rate of 2.5 events per unit and 20 events,
#  using the score method
prec_rate(2.5, x = 20, met = "score")
#> 
#>      precision for a rate with score confidence interval 
#> 
#>     r     radj  x time conf.width conf.level      lwr      upr
#> 1 2.5 2.740091 20    8   2.243301       0.95 1.618441 3.861742
#> 
#> NOTE: 'x / r' units of time are needed to accumulate 'x' events.
#> 
# number of events to yield a CI width of 2.243 for a rate of 2.5 events per
#  unit and 20 events, using the score method
prec_rate(2.5, conf.width = 2.243, met = "score")
#> 
#>      sample size for a rate with score confidence interval 
#> 
#>     r    radj        x     time conf.width conf.level     lwr     upr
#> 1 2.5 2.74003 20.00514 8.002055      2.243       0.95 1.61853 3.86153
#> 
#> NOTE: 'x / r' units of time are needed to accumulate 'x' events.
#> 
# confidence interval width for a rate of 2.5 events per unit and 20 events,
#  using the exact method
prec_rate(2.5, x = 20, met = "exact")
#> 
#>      precision for a rate with exact confidence interval 
#> 
#>     r radj  x time conf.width conf.level      lwr      upr
#> 1 2.5  2.5 20    8   2.333982       0.95 1.527065 3.861047
#> 
#> NOTE: 'x / r' units of time are needed to accumulate 'x' events.
#> 
# vs and wald have the same conf.width, but different lwr and upr
prec_rate(2.5, x = 20, met = "vs")
#> 
#>      precision for a rate with vs confidence interval 
#> 
#>     r     radj  x time conf.width conf.level      lwr      upr
#> 1 2.5 2.620046 20    8   2.191306       0.95 1.524392 3.715699
#> 
#> NOTE: 'x / r' units of time are needed to accumulate 'x' events.
#> 
prec_rate(2.5, x = 20, met = "wald")
#> 
#>      precision for a rate with wald confidence interval 
#> 
#>     r radj  x time conf.width conf.level      lwr      upr
#> 1 2.5  2.5 20    8   2.191306       0.95 1.404347 3.595653
#> 
#> NOTE: 'x / r' units of time are needed to accumulate 'x' events.
#>