generate simulation parameter dataframe

generate simulation parameter dataframe

sim_df(
  dist_df = default_parameters,
  k = c(3, 7, 20),
  tau_sq = seq(0, 0.4, by = 0.2),
  effect_ratio = c(1, 1.2, 1.5),
  min_n = 20,
  max_n = 200,
  prop = 0.5,
  prop_error = 0.1
)

Arguments

dist_df

A dataframe. with one column for distribution, and one column for the parameters. Defaults to default_parameters. Note that the par arguments can be changed, but only the distributions presented in default_parameters have been implemented.

k

Simulate for different numbers of studies.

tau_sq

Variance \(\gamma_k \sim N(0, \tau^2)\) associated with the random effect

effect_ratio

Ratio of population effects intervention / control

min_n

lower bound for sample sizes, defaults to 20

max_n

upper bound for sample sizes, defaults to 200

prop

proportion of n we expect

prop_error

what do we expect 90% of proportions to fall within?

See also

Other simulation Functions that contribute to simulation pipeline.: beta_par(), default_parameters, intervention_proportion(), sim_n(), sim_sample()