Package index • LittleHelpers

Multilevel helpers

Explore multilevel data: lmer helpers, centering, exploring parameters

add_term(): Add or remove terms to a lmer formula string

cor_between(): Correlation between group aggregates

cor_within(): Within-group correlations

explained_variance(): Computes pseudo-R2 by subtracting residual variances

grand_center(): Grand mean centering of one or more variables

group_center(): Group-centering of one or more variables

aggr_and_merge(): Creates country level variables by aggregating individual level variables

potential_interactions(): Potential cross-level interactions

potential_interactions_ind(): Potential individual-level interactions for lmer model

search_random(): Find random effects across fixed

vif_mer(): Compute variance inflation factor for mer objects

SEM helpers

Handy SEM helpers

add_all_indir_and_tot(): Add all possible indirect and total effects to the `lavaan` formula

check_mplus_model(): Check NDP related to residuals and correlations of models read by 'readModels'

diff_test_mlr(): Loglikelihood test for MLR estimator

diff_test_mlr_manual(): Loglikelihood test for MLR estimator - wrapper

each_param_psr_mplus(): Various versions of PSR

extract_mlefa(): Extracts fit indices of the Multilevel EFA (Mplus output)

gamma_hat_mplus(): Computes Gamma fit index for SEM models fit in Mplus

get_params_mplus(): Extracts parameters from Bayesian models produces by Mplus where 'readModels' cannot help

get_psr(): get PSR from an mplus output file

lav_compare(): Combine fit measures form several models and compare

manipulate_mplus(): manipulate mplus file

partable_mplus(): Summarize parameters from several Mplus models read by 'readModels'

sem_tab(): SEM tab

tech11_14(): Extracts Tech11 and Tech14 (Tests for mixture models)

brmsea(): Hoot's BRMSEA

Tools for labelled data and Rstudio viewer

Formatting, showing results, and handling labels

label_book(): Create a codebook, table of labels to explore variables and values in your data

drop_labs(): Get rid of the labels

label_table(): Alias for label_book

lab_to_fac(): Convert labelled variable to a factor with corresponding values

unhaven(): Drop the structure added by haven package

untibble(): Get rid of the tibble

eststar(): Quickly generate string from estimates and p-values

f(): Format the number quickly and remove zero before dot

sig_to_bold(): Conditional formatting

pvalue_to_stars(): Convert numbers to stars

df_to_viewer(): Shows data.frame or model(s) in RStudio viewer

lmer_table(): Function producing a tidy table for many multilevel regressions (lmer fitted objects)

Plots and diagrams

Visualize multilevel and SEM

graph_means_ci(): Graph means w/CIs

lav_to_graph(): Create a Graphviz path diagram using lavaan syntax

lav_to_draw(): Convert lavaan to draw.io diagram

plef(): Simple interaction plot with nice defaults

plot_latent_means(): Plot latent means

random_interaction(): Plot cross-level interactions for mer objects

random_plot(): Plot random effects and interactions for lmer objects

scatter_means_ci(): Computes means by group and plots them in as a scatterplot

sig_seg(): Prepares data for significance staples on ggplot

stacked_bar(): Quick stacked bar plot

theme_mr(): Clean and precise theme

traceplots_mplus(): Extract and export Mplus trace and autocorrelation plots into pdf

Miscellaneous

Convenience functions and shortcuts

cor_table(): Correlation table with stars

compare_cor(): Compare two correlation matrices

crosstab(): Easy cross-tabulation with labels

match_named_vectors(): Match named vectors to a data.frame

replace_by_table(): Replace by table

reverse(): Reverse values and value labels

mean_se_lower_upper(): Means and SEs

se(): Standard err of mean

get_net(): Make a quick network graph

na_tab(): Prints the number and percent of NAs in a dataframe

verb(): Convenience function for logging the code

ess_values(): Compute basic values indices as measured in European Social Survey

values: List of Schwartz values