Collection of Convenient Functions for Common Statistical Computations


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Documentation for package ‘sjstats’ version 0.13.0

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sjstats-package Collection of Convenient Functions for Common Statistical Computations
anova_stats Effect size statistics for anova
autocorrelation Check model assumptions
bootstrap Generate nonparametric bootstrap replications
boot_ci Standard error and confidence intervals for bootstrapped estimates
boot_est Standard error and confidence intervals for bootstrapped estimates
boot_p Standard error and confidence intervals for bootstrapped estimates
boot_se Standard error and confidence intervals for bootstrapped estimates
check_assumptions Check model assumptions
chisq_gof Chi-square goodness-of-fit-test
cod Tjur's Coefficient of Discrimination
cohens_f Effect size statistics for anova
converge_ok Convergence test for mixed effects models
cramer Measures of association for contingency tables
cronb Check internal consistency of a test or questionnaire
cv Coefficient of Variation
cv_compare Test and training error from model cross-validation
cv_error 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 Effect size statistics for anova
find_beta Determining distribution parameters
find_beta2 Determining distribution parameters
find_cauchy Determining distribution parameters
find_normal Determining distribution parameters
get_re_var Random effect variances
gmd Gini's Mean Difference
grpmean Summary of mean values by group
hdi Compute high density intervals (HDI) for MCMC samples
heteroskedastic Check model assumptions
hoslem_gof Hosmer-Lemeshow Goodness-of-fit-test
icc Intraclass-Correlation Coefficient
inequ_trend Compute trends in status inequalities
is_prime Find prime numbers
is_singular Convergence test for mixed effects models
link_inverse Access information from model objects
md Sum, mean and median for vectors
mean_n Row means with min amount of valid values
mic Check internal consistency of a test or questionnaire
mn Sum, mean and median for vectors
model_frame Access information from model objects
mse Compute model quality
multicollin Check model assumptions
mwu Mann-Whitney-U-Test
nhanes_sample Sample dataset from the National Health and Nutrition Examination Survey
normality Check model assumptions
odds_to_rr Get relative risks estimates from logistic regressions or odds ratio values
omega_sq Effect size statistics for anova
or_to_rr Get relative risks estimates from logistic regressions or odds ratio values
outliers Check model assumptions
overdisp Check overdispersion of GL(M)M's
pca Tidy summary of Principal Component Analysis
pca_rotate Tidy summary of Principal Component Analysis
phi Measures of association for contingency tables
pred_accuracy Accuracy of predictions from model fit
pred_vars Access information from model objects
prop Proportions of values in a vector
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 Check internal consistency of a test or questionnaire
resp_val Access information from model objects
resp_var Access information from model objects
re_var Random effect variances
rmse Compute model quality
robust Robust standard errors for regression models
rope Compute high density intervals (HDI) for MCMC samples
rse Compute model quality
scale_weights Rescale design weights for multilevel analysis
sd_pop Calculate population variance and standard deviation
se Standard Error for variables or coefficients
se_ybar Standard error of sample mean for mixed models
sjstats Collection of Convenient Functions for Common Statistical Computations
sm Sum, mean and median for vectors
smpsize_lmm Sample size for linear mixed models
split_half Check internal consistency of a test or questionnaire
std_beta Standardized beta coefficients and CI of linear and mixed models
svy Robust standard errors for regression models
svyglm.nb Survey-weighted negative binomial generalised linear model
svy_md Weighted statistics for variables
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_names Access information from model objects
var_pop Calculate population variance and standard deviation
weight Weight a variable
weight2 Weight a variable
wtd_sd Weighted statistics for variables
wtd_se Weighted statistics for variables
xtab_statistics Measures of association for contingency tables
zero_count Check overdispersion of GL(M)M's