© 2010-2024,

Kristopher J. Preacher

Kristopher J. Preacher

- Sobel test calculator for simple mediation effects.
- Chi-square tests of goodness of fit and independence.
- Correlation test for independent correlation coefficients.
- Correlation test for dependent correlations (one variable in common).
- Correlation test for dependent correlations (no variable in common).
- Fisher's exact test for determining independence in 2 x 2 tables.
- Power curve plotting utility for RMSEA.
- Power analysis and sample size determination for RMSEA.
- Monte Carlo calculator for creating sampling distributions and confidence intervals for correlation coefficients.
- Monte Carlo calculator for creating sampling distributions and confidence intervals for indirect effects.
- Monte Carlo calculator for creating sampling distributions and confidence intervals for indirect effects in 1-1-1 multilevel models.
- Interaction Utilities to accompany Bauer & Curran (2006), Curran, Bauer, & Willoughby (2006), and Preacher, Curran, & Bauer (2006) papers on probing interaction effects.

- Why do we divide by
*n*-1 when computing a sample variance? Here is a step-by-step proof that dividing by*n*leads to a biased estimate, whereas dividing by*n*-1 leads to an unbiased estimate. - A primer on interaction effects in multiple linear regression containing a review of key concepts related to interaction effects in MLR.
- In SEM and factor analysis, how does one derive a discrepancy function from a likelihood function? Here is a derivation of the ML discrepancy function from likelihoods, with or without a mean structure in the model, and using either raw data or a covariance matrix as input.