PRDA {PRDA}R Documentation

PRDA: Prospective and Retrospective Design Analysis.

Description

Given an hypothetical value of effect size, PRDA performs a prospective or retrospective design analysis to evaluate the inferential risks (i.e., power, Type M error, and Type S error) related to the study design. See vignette("PRDA") for a brief introduction to Design Analysis.

Details

PRDA package can be used for Pearson's correlation between two variables or mean comparisons (i.e., one-sample, paired, two-sample, and Welch's t-test) considering an hypothetical value of \rho or Cohen's d respectively. See vignette("retrospective") for more details.

Functions

In PRDA there are two main functions:

Hypothetical Effect Size

The hypothetical population effect size can be defined as a single value according to previous results in the literature or experts indications. Alternatively, PRDA allows users to specify a distribution of plausible values to account for their uncertainty about the hypothetical population effect size. To know how to specify the hypothetical effect size according to a distribution and an example of application see vignette("retrospective").

References

Altoè, G., Bertoldo, G., Zandonella Callegher, C., Toffalini, E., Calcagnì, A., Finos, L., & Pastore, M. (2020). Enhancing Statistical Inference in Psychological Research via Prospective and Retrospective Design Analysis. Frontiers in Psychology, 10. https://doi.org/10.3389/fpsyg.2019.02893

Bertoldo, G., Altoè, G., & Zandonella Callegher, C. (2020, June 15). Designing Studies and Evaluating Research Results: Type M and Type S Errors for Pearson Correlation Coefficient. Retrieved from https://psyarxiv.com/q9f86/

Gelman, A., & Carlin, J. (2014). Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors. Perspectives on Psychological Science, 9(6), 641–651. https://doi.org/10.1177/1745691614551642


[Package PRDA version 1.0.0 Index]