This function performs sample size computation for testing Pearson's correlation coefficient based on precision requirements (i.e., typeIrisk, typeIIrisk and an effect size).
1 2 3 
rho 
a number indicating the correlation coefficient under the null hypothesis, ρ.0. 
delta 
minimum difference to be detected, δ. 
alternative 
a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". 
alpha 
typeIrisk, α. 
beta 
typeIIrisk, β. 
output 
logical: if 
Returns an object of class size
with following entries:
call  function call 
type  type of the test (i.e., correlation coefficient) 
spec  specification of function arguments 
res  list with the result, i.e., optimal sample size 
Takuya Yanagida takuya.yanagida@univie.ac.at,
Rasch, D., Kubinger, K. D., & Yanagida, T. (2011). Statistics in psychology  Using R and SPSS. New York: John Wiley & Sons.
Rasch, D., Pilz, J., Verdooren, L. R., & Gebhardt, G. (2011). Optimal experimental design with R. Boca Raton: Chapman & Hall/CRC.
seqtest.cor
, size.mean
, size.prop
, print.size
1 2 3 4 5 6 7 8 9 10 11  #
# H0: rho = 0.3, H1: rho != 0.3
# alpha = 0.05, beta = 0.2, delta = 0.2
size.cor(rho = 0.3, delta = 0.2, alpha = 0.05, beta = 0.2)
#
# H0: rho <= 0.3, H1: rho > 0.3
# alpha = 0.05, beta = 0.2, delta = 0.2
size.cor(rho = 0.3, delta = 0.2, alternative = "greater", alpha = 0.05, beta = 0.2)

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
All documentation is copyright its authors; we didn't write any of that.