4.3.2020

This script calculates power for observing a significant effect for known correlates.

Aric R^2 values from Ryan:

library(knitr)
agemult = 0.008552
ageadj = 0.007883

sexmult = 0.02774
sexadj = 0.02709

wbcmult = 0.04947
wbcadj = 0.04883

# Calculate effect size measures
# https://www.statmethods.net/stats/power.html
agef2 = agemult/(1-agemult)
sexf2 = sexmult/(1-sexmult)
wbcf2 = wbcmult/(1-wbcmult)

Use the pwr package:

library(pwr)

# covariates used: age, sex, 
# u = number of covariates, not including intercept ((mtDNA ~ Neutrophils/SEX/AGE + HSC + Megakaryocytes + COHORT + TRISCHD)) = 4
# v = n - u - 1  = 418 - 4 - 1 = 391

pwr.f2.test(u = 4, v = 413, f2 = agef2, sig.level = .05)

## 
##      Multiple regression power calculation 
## 
##               u = 4
##               v = 413
##              f2 = 0.008625768
##       sig.level = 0.05
##           power = 0.2868267

pwr.f2.test(u = 4, v = 413, f2 = sexf2, sig.level = .05)

## 
##      Multiple regression power calculation 
## 
##               u = 4
##               v = 413
##              f2 = 0.02853146
##       sig.level = 0.05
##           power = 0.7944676

pwr.f2.test(u = 4, v = 413, f2 = wbcf2, sig.level = .05)

## 
##      Multiple regression power calculation 
## 
##               u = 4
##               v = 413
##              f2 = 0.05204465
##       sig.level = 0.05
##           power = 0.9748073

make a table:

covs = c('Age', 'Sex (Female)', 'Neutrophils')
gtex = c(-0.06, 0.14, -0.19)
aric = c(-0.02, 0.46, -0.14)
gtexp = c(0.19, 0.17, 5e-5)
aricp = c(0.004, 9.95e-14,9.97e-16)
power = c('28.68%', '79.44%', '97.48%')

show = data.frame(Covariate = covs, gtex = gtex, aric = aric, gtexp= gtexp, aricp = aricp, power = power)

library(htmlTable)
htmlTable(show, rnames = rep('', nrow(show)), header = c('Covariate', 'GTEx effect estimate', 'ARIC effect estimate', 'GTEx p-value', 'ARIC p-value', 'Power'))

	Covariate	GTEx effect estimate	ARIC effect estimate	GTEx p-value	ARIC p-value	Power
	Age	-0.06	-0.02	0.19	0.004	28.68%
	Sex (Female)	0.14	0.46	0.17	9.95e-14	79.44%
	Neutrophils	-0.19	-0.14	5e-05	9.97e-16	97.48%