Estimate sample size required to achieve a target statistical power

This function estimates the sample size required to achieve a specified target power using predictions from a fitted GAM/SCAM power model. The function evaluates predicted power across a grid of candidate sample sizes and identifies the smallest sample size for which the predicted power reaches or exceeds the target value. Linear interpolation is then used on the log2(sample size) scale to obtain a more precise estimate.

Usage

sample_size_ss_interp(
  target_power,
  logmean,
  abs_lfc,
  model,
  xmin = log2(5),
  xmax = log2(500),
  ngrid = 1000
)

Arguments

target_power

Numeric value specifying the desired statistical power.

logmean

Numeric value representing the log mean abundance.

abs_lfc

Numeric value representing the absolute log fold change.

model

A fitted GAM/SCAM model used to predict statistical power.

xmin

Numeric value giving the minimum log2(sample size) considered in the search. Default is log2(5).

xmax

Numeric value giving the maximum log2(sample size) considered in the search. Default is log2(500).

ngrid

Integer specifying the number of grid points used when searching for the sample size solution. Default is 1000.

Value

A numeric value representing the estimated sample size required to achieve the target power. Returns NA if the target power is not reached within the specified search range.

Details

The function first constructs a grid of candidate sample sizes on the log2 scale between xmin and xmax. Predicted power values are then obtained from the fitted model for each grid point. The smallest sample size at which the predicted power reaches the target value is identified, and linear interpolation is used to refine the estimate.