All functions

auto_prior()

Create default priors for brms-models

bootstrap()

Generate nonparametric bootstrap replications

boot_ci() boot_se() boot_p() boot_est()

Standard error and confidence intervals for bootstrapped estimates

chisq_gof()

Compute model quality

cv()

Compute model quality

cv_error() cv_compare()

Test and training error from model cross-validation

deff()

Design effects for two-level mixed models

efc

Sample dataset from the EUROFAMCARE project

eta_sq() omega_sq() epsilon_sq() cohens_f() anova_stats()

Effect size statistics for anova

find_beta() find_beta2() find_cauchy() find_normal()

Determining distribution parameters

fish

Sample dataset

gmd()

Gini's Mean Difference

grpmean()

Summary of mean values by group

inequ_trend()

Compute trends in status inequalities

is_prime()

Find prime numbers

mean_n()

Row means with min amount of valid values

mediation()

Summary of Bayesian multivariate-response mediation-models

mwu()

Mann-Whitney-U-Test

nhanes_sample

Sample dataset from the National Health and Nutrition Examination Survey

odds_to_rr() or_to_rr()

Get relative risks estimates from logistic regressions or odds ratio values

overdisp() zero_count() converge_ok() is_singular() reliab_test() split_half() cronb() difficulty() mic() pca() pca_rotate() n_eff() mcse() pred_vars() model_family() model_frame() resp_val() resp_var() grp_var() re_grp_var() var_names() pred_accuracy() outliers() heteroskedastic() autocorrelation() normality() multicollin() check_assumptions() r2() icc() hdi() rope()

Deprecated functions

prop() props()

Proportions of values in a vector

p_value()

Get p-values from regression model objects

robust() svy()

Robust standard errors for regression models

scale_weights()

Rescale design weights for multilevel analysis

se()

Standard Error for variables or coefficients

se_ybar()

Standard error of sample mean for mixed models

sjstats-package

Collection of Convenient Functions for Common Statistical Computations

smpsize_lmm()

Sample size for linear mixed models

std_beta()

Standardized beta coefficients and CI of linear and mixed models

svyglm.nb()

Survey-weighted negative binomial generalised linear model

table_values()

Expected and relative table values

tidy_stan()

Tidy summary output for stan models

var_pop() sd_pop()

Calculate population variance and standard deviation

weight() weight2()

Weight a variable

wtd_sd() wtd_mean() wtd_se() wtd_median() svy_md() wtd_chisqtest() wtd_ttest() wtd_mwu() wtd_cor()

Weighted statistics for tests and variables

phi() cramer() xtab_statistics()

Measures of association for contingency tables