Man pages for jbiesanz/fabs
Functions for Applied Behavioural Sciences

boot.fimlBootstraps the full information maximum likelihood regression...
ci_betaCreates a confidence interval for the standardized regression...
ci_dCreates a confidence interval for the standardized mean...
ci_fCreates a confidence interval for Cohen's f.
ci_rCreates a confidence interval for the correlation.
ci_r2Creates a confidence interval for the squared multiple...
desired_ep_dDetermines the required sample size in a future study to...
desired_ep_FtestDetermines the required sample size in a future study to...
desired_ep_rDetermines the required sample size in a future study to...
desired_ep_tDetermines the required sample size in a future study to...
d_robustEstimates the robust standardized mean difference based on...
em.summaryFunction to return the EM means and standard deviations using...
ep_FtestDetermines the expected power in a future study with...
ep_rDetermines the expected power a future study with a specified...
fiml.regressionWrapper function to estimate an lm() model in lavaan under...
norm.regressionFunction to automate multiple imputation (MI) for missing...
posterior_Cohen_fSamples from the posterior distribution of Cohen's f....
posterior_dSamples from the posterior distribution of the standardized...
posterior_rSamples from the posterior distribution of the correlation...
posterior_tSamples from the posterior distribution of the noncentral...
robust_lm_inferencesEstimates a series of robust regressions for a specified...
scale.all.variablesFunction to standardize all variables based on supplied mean...
jbiesanz/fabs documentation built on Nov. 17, 2018, 9 a.m.