wp.mc.t: Power analysis for t-test based on Monte Carlo simulation

Description Usage Arguments References Examples

View source: R/webpower.R

Description

Power analysis for t-test based on Monte Carlo simulation

Usage

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wp.mc.t(n = NULL, R0 = 1e+05, R1 = 1000, mu0 = 0, mu1 = 0, 
sd = 1, skewness = 0, kurtosis = 3, alpha = 0.05, 
type = c("two.sample", "one.sample", "paired"), 
alternative = c("two.sided", "less", "greater"))

Arguments

n

Sample size

R0

Number of replications under the null

R1

Number of replications

mu0

Population mean under the null

mu1

Population mean under the alternative

sd

Standard deviation

skewness

Skewness

kurtosis

kurtosis

alpha

Significance level

type

Type of anlaysis

alternative

alternative hypothesis

References

Zhang, Z., & Yuan, K.-H. (2018). Practical Statistical Power Analysis Using Webpower and R (Eds). Granger, IN: ISDSA Press.

Examples

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########## Chapter 16. Monte Carlo t-test #############
wp.mc.t(n=20 , mu0=0, mu1=0.5, sd=1, skewness=0, 
kurtosis=3, type = c("one.sample"), alternative = c("two.sided"))

wp.mc.t(n=40 , mu0=0, mu1=0.3, sd=1, skewness=1, 
kurtosis=6, type = c("paired"), alternative = c("greater"))

wp.mc.t(n=c(15, 15), mu1=c(0.2, 0.5), sd=c(0.2, 0.5), 
skewness=c(1, 2), kurtosis=c(4, 6), type = c("two.sample"), alternative = c("less"))

WebPower documentation built on May 1, 2019, 8:19 p.m.