| BICBF | Use delta-BIC to approximate Bayes Factors for model... |
| bootD_equalSS | Bootstrap equal-sample-size Cohen's d |
| brm_optimizing | Maximum-likelihood fitting of a brm-style model |
| d1iso | Extract first dimension using nonmetric scaling |
| dat2mvt | Fit multivariate skew-T distribution to a numeric dataset |
| dat_cochraneEtAl_2019_PLOSOne | Data from Cochrane, Simmering, & Green (2019), PLOS One |
| ddm_dr_lm | Fit linear predictors of DDM drift rate |
| df_xfm | Transform a numeric data frame or matrix using the... |
| findLowerRT | Find Lower RT bound, return the bound and a vector of "keep... |
| fitQuickfun | Fit a Quick [see Ahissar & Hochstein] function, given data |
| getTime | Get the current date and time in an easy-to-use format |
| invertYJ | Invert a Yeo-Johnson transformation |
| isOutlier | Find multivariate outliers (Leys et al., 2018, JESP) |
| lmer_cohenD | Find Cohen's D for lmer model |
| oos_partial | Estimate matrix of bivariate out-of-sample variance explained |
| pairsplot | Create a 'psych::pairs.panels()' plot with standard... |
| r2bf | Convert correlation _r_ to a Bayes Factor |
| resetSeed | Re-randomize seed |
| rmse | Find Root Mean Squared Error |
| robustCor | Find a robust bootstrapped correlation |
| robustLM_bayes | Fit a robust model, with fully Bayesian model comparisons |
| scale2 | Scale a variable to a new mean and standard deviation |
| scatterMat | Create a matrix of scatter plots, with each row and each... |
| shinyReg | Visualize two-predictor regression using shiny |
| sim_dat | Simulate new data from a numeric and/or logical data frame or... |
| sim_from_dat | Simulate new data from a dataset's quantiles |
| sourceIfChanged | Source a file, but only if it changed from the last time you... |
| trialWDM | Find by-trial Wiener Diffusion Model parameters |
| wapply | Apply a function to windows of the data |
| wilcZ | Wilcoxon tests, returning a z value that respects the sign of... |
| windowDeriv | Get by-time Level, Change and Acceleration |
| windowWDM | Find a vector of Wiener Diffusion Model parameters |
| YeoJohn | Apply optimal Yeo-Johnson transformation to a numeric vector |
| zeroOneNorm | Normalize a vector to be between .001 and .999 |
