Produce a sample size table giving the minimum sample size per cluster for given values of the ICC and the prevalence threshold against which we are comparing.
get_sample_size_table(
prevalence = seq(0, 0.2, 0.01),
ICC = 0.05,
prev_thresh = 0.05
)the assumed true prevalence of pfhrp2/3 deletions in the
domain. Allowed values are anything in seq(0, 0.2, 0.01), including
vectors of values.
the assumed intra-cluster correlation. Allowed values are" {0, 0.01, 0.02, 0.05, 0.1, 0.2}.
the prevalence threshold against which we are comparing. Allowed values are: {0.05, 0.08, 0.1}.
The function get_power_threshold() was run over a large range
of parameter combinations and results were stored within the df_sim
object (see ?df_sim). These simulations were then used to produce
minimum sample size estimates by linear interpolation that were stored
within the df_ss object (see ?df_ss). This function provides
a simple way of querying the df_ss object for given parameter
values.
get_sample_size_table()
#> # A tibble: 19 × 21
#> n_clust `0.01` `0.02` `0.03` `0.04` `0.05` `0.06` `0.07` `0.08` `0.09` `0.1`
#> <int> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2 NA NA NA NA NA NA NA NA NA NA
#> 2 3 NA NA NA NA NA NA NA NA NA NA
#> 3 4 NA NA NA NA NA NA NA NA NA NA
#> 4 5 NA NA NA NA NA NA NA NA NA 496
#> 5 6 NA NA NA NA NA NA NA NA NA 113
#> 6 7 NA NA NA NA NA NA NA NA NA 68
#> 7 8 NA NA NA NA NA NA NA NA 416 51
#> 8 9 NA NA NA NA NA NA NA NA 138 37
#> 9 10 NA NA NA NA NA NA NA NA 85 30
#> 10 11 NA NA NA NA NA NA NA NA 66 25
#> 11 12 NA NA NA NA NA NA NA NA 45 22
#> 12 13 NA NA NA NA NA NA NA NA 40 17
#> 13 14 NA NA NA NA NA NA NA 438 34 15
#> 14 15 NA NA NA NA NA NA NA 179 29 14
#> 15 16 NA NA NA NA NA NA NA 122 28 13
#> 16 17 NA NA NA NA NA NA NA 122 22 11
#> 17 18 NA NA NA NA NA NA NA 84 21 11
#> 18 19 NA NA NA NA NA NA NA 70 19 10
#> 19 20 NA NA NA NA NA NA NA 67 18 9
#> # ℹ 10 more variables: `0.11` <dbl>, `0.12` <dbl>, `0.13` <dbl>, `0.14` <dbl>,
#> # `0.15` <dbl>, `0.16` <dbl>, `0.17` <dbl>, `0.18` <dbl>, `0.19` <dbl>,
#> # `0.2` <dbl>