| Title: | Empirical Small Telescopes Analysis |
|---|---|
| Description: | We provide functions to perform an empirical small telescopes analysis. This package contains 2 functions, SmallTelescopes() and EstimatePower(). Users only need to call SmallTelescopes() to conduct the analysis. For more information on small telescopes analysis see Uri Simonsohn (2015) <doi:10.1177/0956797614567341>. |
| Authors: | John Ruscio [aut, cre], Samantha Costigan [ctb] |
| Maintainer: | John Ruscio <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 1.0.4 |
| Built: | 2025-02-28 08:09:34 UTC |
| Source: | CRAN |
Estimate statistical power of an effect size parameter by simulation using original sample size.
EstimatePower(data, n.original, B.power, analysis, n.rows, alpha)EstimatePower(data, n.original, B.power, analysis, n.rows, alpha)
data |
Dataset (matrix). |
n.original |
The sample size of the original analysis (scalar). |
B.power |
The number of samples to be simulated (scalar). |
analysis |
Function to produce a p value and an effect size estimate. |
n.rows |
The number of rows per subject in the dataset (scalar) |
alpha |
Set alpha level for analysis (scalar) |
Power estimate generated through simulation (scalar).
# create or import dataset example.data <- matrix(rnorm(50), 25, 2) # estimate statistical power EstimatePower( data = example.data, n.original = 10, analysis = function(data) { corr <- cor.test(data[,1], data[,2]) return(list(effect.size = corr$estimate, p.value = corr$p.value)) }, B.power = 100, n.rows = 1, alpha = 0.05)# create or import dataset example.data <- matrix(rnorm(50), 25, 2) # estimate statistical power EstimatePower( data = example.data, n.original = 10, analysis = function(data) { corr <- cor.test(data[,1], data[,2]) return(list(effect.size = corr$estimate, p.value = corr$p.value)) }, B.power = 100, n.rows = 1, alpha = 0.05)
Estimate statistical power for point estimate of effect size plus the lower and upper bounds of a confidence interval.
SmallTelescopes( data, analysis, n.original, B.CI = 10000, CI.level = 0.9, B.power = 10000, alpha = 0.05, n.rows = 1, seed = 1 )SmallTelescopes( data, analysis, n.original, B.CI = 10000, CI.level = 0.9, B.power = 10000, alpha = 0.05, n.rows = 1, seed = 1 )
data |
Dataset (matrix). |
analysis |
Function to produce a p value and an effect size estimate. |
n.original |
The sample size of the original analysis (scalar). |
B.CI |
The number of simulated samples used to construct CI (scalar); default = 10,000. |
CI.level |
The confidence level of the interval (scalar); default = .90. |
B.power |
The number of samples to be simulated (scalar); default = 10,000. |
alpha |
Set alpha level for analysis (scalar); default = 0.05. |
n.rows |
The number of rows per subject in the dataset (scalar); default = 1. |
seed |
Allows randomly generated numbers to be reproducible (scalar); default = 1. |
Displays statistical power for point estimate of an effect size plus the lower and upper bounds of a confidence interval. List contains the following components:
n.replication |
The sample size of the replication analysis. |
n.original |
The sample size of the original analysis. |
B.CI |
The number of simulated samples used to construct CI. |
CI.level |
The confidence level of the interval. |
B.power |
The number of samples simulated. |
p.value |
The p value calculated from the replication data |
es.estimate |
Point estimate of effect size. |
es.power |
Estimated power for the point estimate of effect size. |
CI.lower.estimate |
Effect size estimate at the lower bound of the CI. |
CI.lower.power |
Estimated power for the lower bound of the CI. |
CI.upper.estimate |
Effect size estimate at the upper bound of the CI. |
CI.upper.power |
Estimated power for the upper bound of the CI. |
# create or import dataset example.data <- matrix(rnorm(50), 25, 2) # conduct empirical small telescopes analysis SmallTelescopes( data = example.data, analysis = function(data) { corr <- cor.test(data[,1], data[,2]) return(list(effect.size = corr$estimate, p.value = corr$p.value)) }, n.original = 10, B.CI = 100, B.power = 100)# create or import dataset example.data <- matrix(rnorm(50), 25, 2) # conduct empirical small telescopes analysis SmallTelescopes( data = example.data, analysis = function(data) { corr <- cor.test(data[,1], data[,2]) return(list(effect.size = corr$estimate, p.value = corr$p.value)) }, n.original = 10, B.CI = 100, B.power = 100)