p_value {attenuation}R Documentation

Calculate the p-value for an attenuated correlation coefficient.


This function calculates four types of p-values for correlations coefficients corrected for attenuation, chosen in "method". The different p-values are described in Moss (2019). "corr" is the correlation based p-value, "cronbach" is the Cronbach alpha based p-value, "HS" is the Hunter-Schmidt p-value, while "free" is the correlation based p-value without positive constraints.


p_value(rho, r, N, method = "corr", k = NULL)



Numeric vector in [-1,1]. The correlation under the null hypothesis.


Numeric vector of three elements in [-1,1]. r[1] is the correlation between the noisy measures X' and Y', r[2] is the correlation between the noisy X' and the true X, while r[3] is the correlation between the noisy Y' and the true Y. They are the square root of the reliabilities. Must be positive method to "corr" and "cronbach".


Numeric vector of three positive integers. N[i] is the sample size for r[i].


The type of p-value. Can be "corr", "cronbach", "HS" or "free". See the details.


Numeric vector of two positive integers. k[i] is the number of testlets for the for r[i+1]. Only needed for method "cronbach".


Numeric in [0, 1]. The p-value under the null-hypothesis that the true correlation is rho.


    r = c(0.20, sqrt(0.45), sqrt(0.55))
    N = c(100, 100, 100)
    p_value(rho = 0, r, N) # Tests rho = 0.

[Package attenuation version 1.0.0 Index]