install.packages("pwr")
library(pwr)
INPUT THE SAMPLE SIZES, MEAN CALVING SUCCESS AND STANDARD ERRORS FROM MANN, ET AL. 2008.
# Non-spongers:
n_nonspongers=116
mean_CS_nonspongers=0.132
SE_CS_nonspongers=0.008
# Spongers:
n_spongers=16
mean_CS_spongers=0.156
SE_CS_spongers=0.018
#### CALCULATE DIFFERENCE IN MEASURED CALVING SUCCESS BETWEEN SPONGERS AND NONSPONGERS
percent_increase=(mean_CS_spongers - mean_CS_nonspongers)/mean_CS_nonspongers
print(paste("Percent Increase in Sponger Calving Success: ", 100*round(percent_increase, digits=2), "%"))
CONVERT STANDARD ERRORS TO STANDARD DEVIATIONS
SD_CS_nonspongers=SE_CS_nonspongers*sqrt(n_nonspongers)
SD_CS_spongers=SE_CS_spongers*sqrt(n_spongers)
CALCULATE TERMS FOR POWER ANALYSIS
SS_within=(n_nonspongers-1)*SD_CS_nonspongers^2 + (n_spongers-1)*SD_CS_spongers^2
df_within=n_nonspongers + n_spongers - 2
SD_within=sqrt(SS_within/df_within)
PERFORM POWER ANALYSIS FOR A TWO-SIDED TEST
## RUN POWER ANALYSIS
power_test_results=pwr.t2n.test(n1=n_nonspongers, n2=n_spongers, d=NULL, sig.level = 0.05, power = 0.8,