pilsecond: prior-informed Lambda second distribution.

In CohensdpLibrary: Cohen's D_p Computation with Confidence Intervals

prior-informed Lambda second distribution.

Description

This distribution extend the lambda second distribution introduced in \insertCitec22b;textualCohensdpLibrary as the exact solution to the predictive distribution of the Cohen's dp in repeated-measure when the population correlation is known. A more elegant notation was provided in \insertCitel22;textualCohensdpLibrary. The prior-informed lambda prime is a bayesian extension to the lambda prime distribution in the case where the population rho is not known. It is then replaced by a prior which indicates the probability of a certain rho given the observed correlation r.

Usage

ppilsecond(delta, n, d, r) 
dpilsecond(delta, n, d, r) 
qpilsecond(p,     n, d, r)

Arguments

delta	the parameter of the population whose probability is to assess;
n	the sample size n
d	the observed d_p of the sample;
r	the sample correlation
p	the probability from which a quantile is requested

Details

pilsecond are (p,d,q) functions that compute the prior-informed Lambda-second (L") distribution. This distribution is an generalization of the lambda-prime distribution \insertCitel99CohensdpLibrary. It can take up to two seconds to compute.

Note: the parameters are the raw sample size n, the observed Cohen's dp, and the sample correlation r. All the scaling required are performed within the functions (and so you do not provide degrees of freedom). This is henceforth not a generic lambda-second distribution, but a lambda-second custom-tailored for the problem of standardized mean difference.

Value

     The probability or quantile of a prior-informed Lambda'' distribution.

References

\insertAllCited

Examples

### Note: this distribution can be slow to compute
### dpilsecond(0.25, 9, 0.26, 0.333) # 1.186735
### ppilsecond(0.25, 9, 0.26, 0.333) # 0.5150561
### qpilsecond(0.01, 9, 0.26, 0.333) # -0.7294266

CohensdpLibrary documentation built on Sept. 11, 2024, 7:55 p.m.