All functions

bootstrap()

Generate nonparametric bootstrap replications

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

Standard error and confidence intervals for bootstrapped estimates

check_assumptions() outliers() heteroskedastic() autocorrelation() normality() multicollin()

Check model assumptions

chisq_gof()

Chi-square goodness-of-fit-test

cod()

Tjur's Coefficient of Discrimination

converge_ok() is_singular()

Convergence test for mixed effects models

cv()

Coefficient of Variation

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() cohens_f() anova_stats()

Effect size statistics for anova

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

Determining distribution parameters

gmd()

Gini's Mean Difference

grpmean()

Summary of mean values by group

hdi() equi_test() mcse() mediation() n_eff() rope()

Compute statistics for MCMC samples and Stan models

hoslem_gof()

Hosmer-Lemeshow Goodness-of-fit-test

icc()

Intraclass-Correlation Coefficient

inequ_trend()

Compute trends in status inequalities

is_prime()

Find prime numbers

mean_n()

Row means with min amount of valid values

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()

Check overdispersion of GL(M)M's

pca() pca_rotate()

Tidy summary of Principal Component Analysis

pred_accuracy()

Accuracy of predictions from model fit

pred_vars() resp_var() resp_val() link_inverse() model_frame() model_family() var_names()

Access information from model objects

prop() props()

Proportions of values in a vector

p_value()

Get p-values from regression model objects

r2()

Compute r-squared of (generalized) linear (mixed) models

reliab_test() split_half() cronb() mic()

Check internal consistency of a test or questionnaire

re_var() get_re_var()

Random effect variances

rmse() rse() mse()

Compute model quality

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

typical_value()

Return the typical value of a vector

var_pop() sd_pop()

Calculate population variance and standard deviation

weight() weight2()

Weight a variable

wtd_sd() wtd_se() svy_md()

Weighted statistics for variables

phi() cramer() xtab_statistics()

Measures of association for contingency tables