# power_diff: Power simulation function for a two-group comparison of the... In incubate: Parametric Time-to-Event Analysis with Variable Incubation Phases

 power_diff R Documentation

## Power simulation function for a two-group comparison of the delay parameter.

### Description

There are two ways of operation:

1. `power=NULL` Given sample size `n` it simulates the power.

2. `n=NULL` Given a power an iterative search is started to find a suitable `n` within a specified range.

### Usage

```power_diff(
distribution = c("exponential", "weibull"),
param = "delay",
test = c("bootstrap", "pearson", "moran", "lr", "lr_pp"),
eff = stop("Provide parameters for both group that reflect the effect!"),
n = NULL,
r = 1,
sig.level = 0.05,
power = NULL,
nPowerSim = 1600,
R = 201,
nRange = c(5, 50)
)
```

### Arguments

 `distribution` character. Which assumed distribution is used for the power calculation. `param` character. Parameter name(s) for which to simulate the power. `test` character. Which test to use for this power estimation? `eff` list. The two list elements contain the model parameters (as understood by the delay-distribution functions provided by this package) for the two groups. `n` integer. Number of observations per group for the power simulation or `NULL` when n is to be estimated for a given power. `r` numeric. Ratio of both groups sizes, ny / nx. Default value is 1, i.e., balanced group sizes. Must be positive. `sig.level` numeric. Significance level. Default is 0.05. `power` numeric. `NULL` when power is to be estimated for a given sample size or a desired power is specified (and `n` is estimated). `nPowerSim` integer. Number of simulation rounds. Default value 1600 yields a standard error of 0.01 for power if the true power is 80%. `R` integer. Number of bootstrap samples for test of difference in parameter within each power simulation. It affects the resolution of the P-value for each simulation round. A value of around `R=200` gives a resolution of 0.5% which might be enough for power analysis. `nRange` integer. Admissible range for sample size when power is pre-specified and sample size is requested.

### Details

In any case, the distribution, the parameters that are tested for, the type of test and the effect size (`eff=`) need to be specified. The more power simulation rounds (parameter `nPowerSim=`) the more densely the space of data according to the specified model is sampled.

Note that this second modus (when `n` is estimated) is computationally quite heavy. The iterative search for `n` uses some heuristics and the estimated sample size might actually give a different power-level. It is important to check the stated power in the output. The search algorithm comes to results closer to the power aimed at when the admissible range for sample size (`nRange=`) is chosen sensibly. In case the estimated sample size and the achieved power is too high it might pay off to rerun the function with an adapted admissible range.

### Value

List of results of power simulation. Or `NULL` in case of errors.

incubate documentation built on July 25, 2022, 5:05 p.m.