Estimate power for a range of replicates — est_power_range

Estimate power for range of reps.

est_power_range_lm(
  formula,
  variable_list,
  betas,
  sigma_Cq,
  std_curve_alpha,
  std_curve_beta,
  type = c("exclude_zero", "accuracy"),
  rep_range = seq(2, 20, 2),
  accuracy_level = 0.2,
  conf_level = 0.95,
  n_sim = 200L,
  probs = conf_to_probs(conf_level),
  upper_Cq = 40,
  verbose = FALSE
)

est_power_range_lmer(
  formula,
  variable_list,
  betas,
  sigma_Cq,
  sigma_rand,
  std_curve_alpha,
  std_curve_beta,
  type = c("exclude_zero", "accuracy"),
  rep_range = seq(2, 20, 2),
  accuracy_level = 0.2,
  conf_level = 0.95,
  n_sim = 200L,
  probs = conf_to_probs(conf_level),
  upper_Cq = 40,
  verbose = FALSE
)

Arguments

formula: a model formula, e.g. y ~ x1 + x2. For sim_eDNA_lmer, random intercepts can also be provided, e.g. ( 1 | rep ) .
variable_list: a named list, with the levels that each variable can take. Please note that the variables listed in the formula, including the response variable, must be present in the variable_list or in the X design matrix. Extra variables, i.e. variables which do not occur in the formula, are ignored.
betas: numeric vector, the beta for each variable in the design matrix
sigma_Cq: numeric, the measurement error on CQ.
std_curve_alpha: the alpha value for the formula for converting between log(eDNA concentration) and CQ value
std_curve_beta: the beta value for the formula for converting between log(eDNA concentration) and CQ value
type: either "exclude_zero" or "accuracy". Exclude_zero give the classic power estimate, i.e. whether 0 is in the confidence interval for the estimate ("significant"). Accuracy measures whether the estimated betas are within some percentage of the "true" betas used to simulate the data.
rep_range: vector, a set of the number of iterations to calculate the power for
accuracy_level: numeric, between 0 and 1. The percent of the true betas for the accuracy estimate.
conf_level: numeric, between 0 and 1, representing the percent of the confidence interval to calculate. If probs is not provided, then the interval is assumed to be symetric.
n_sim: integer, the number of simulations to conduct in order to estimate the power.
probs: probabilities for the calculation of the confidence intervals. By default, a symetric set of lower and upper probabilities is constructed by conf_to_probs)
upper_Cq: numeric, the upper limit on CQ detection. Any value of log(concentration) which would result in a value greater than this limit is instead recorded as the limit.
verbose: logical, when TRUE output from rstan::sampling is written to the console.
sigma_rand: numeric vector, the stdev for the random effects. There must be one sigma per random effect specified

Value

list, with each element a vector for the estimated power for each parameter for the corresponding number of replicates.

Details

This function estimates power for an eDNA sampling study for a range of potential reps.

Author

Matt Espe