Package index • fxtas

All functions

add_labels(): Add labels to biomarkers

age_range_medians(): replace decade codes with medians of those decades

all_potential_biomarkers(): Get a list of all potential biomarkers available in dataset

autoplot(<PF>): Create positional variance diagram (PVD)

autoplot(<permutation_test>): Plot the distribution of a permuted test statistic

build_rds_path(): Find path to RDS file with output

build_score_vals(): Construct the table indicating how many levels each biomarker has

clean_gender(): Clean the variable Gender

clean_numeric(): Clean a Numeric Variable

collect_permutation_test_stats(): Collect permutation test statistics

compact_pvd_est_data_prep(): plot_compact_pvd_est: data prep

compact_pvd_facet_labels(): Create facet labels

compile_biomarker_group_list(): Compile a list of biomarker groups

compile_biomarker_groups_table(): Compile biomarker groups table

compute_confus_matrix(): compute confus_matrix as in python version

compute_prob_correct(): Compute each biomarker's probability of being recorded at its baseline level

compute_prob_correct2(): Title

compute_prob_dist(): Computes p(true | obs)? for each biomarker

compute_prob_dist2(): Title

compute_prob_scores(): Compute probabilities of true biomarker levels

compute_score_levels(): Title

construct_biomarker_events_table(): Title

counts_and_pcts(): Compute and paste counts and proportions

create_scid_domains(): Create SCID domain variables

cvic_sim_data: CVIC results from simulated data

define_cases_and_controls(): Categorize `CGG“

.onLoad(): Actions taken when fxtas is loaded

event_order_heatmap(): Event order heatmap

example_likelihoods: example likelihoods matrix

extract_cvic(): Extract CVIC element from an object

extract_figs_from_pickle(): Extact PVDs from pickle file

extract_permuted_likelihoods(): Extract permuted log-likelihoods from pickle files

extract_results_from_pickle(): Extract results from pickle file

extract_results_from_pickles(): Extract results from multiple pickle files

flex_biomarkers_table(): Print method for biomarkers_table

format_likelihoods(): Title

format_results_list(): Format results list extracted from pickle file

get_biomarker_events_table(): Construct biomarker events table

get_levels(): Extract levels from a set of variable names

get_observed_permutation_test_stat(): Compute permutation test statistic

get_visit1(): Get each participant's first visit in dataset

graph_CGG_repeats(): Barplot of CGG repeats

graph_likelihoods_v2(): Title

graph_stage_by_age(): graph stage by age

install_pySuStaIn(): Install the pySuStaIn python package from github

make_biomarkers_table(): Make biomarkers table

make_demographics_table(): Make demographics table

missing_pattern_by_ID(): Title

missingness_reasons.factor(): Compute missingness reasons for a vector of factor variables

missingness_reasons.numeric(): Title

model_dists(): Title

pander(<prob_correct>): Print prob_correct objects as Pandoc markdown tables

permutation_test(): Compute permutation test p-value

plot_CVIC(): Plot a CVIC curve

plot_compact_pvd(): Plot compact PVD tmp function using list of extract_figs_from_pickle

plot_compact_pvd_est(): Plot compact PVD with point estimates only

plot_compact_pvd_est2(): Plot SuStaIn Sequential Estimate

plot_cv_loglik(): Plot cross-validated per-fold log-likelihood distributions

plot_heatmap(): Title

plot_permutation_results(): Plot permutation test results

plot_positional_var(): Plot positional variance diagram

print(<permutation_test>): print method for "permutation_test" objects

print_PVDs(): Print a list of PVDs

pvd_lineplot(): Plot change in Stage ranking

remove_missingness_reason_vars(): Remove variable

replace_missing_codes(): Replace missing codes in a vector of factor variables

replace_missing_codes_with_NAs(): Replace missing codes with NAs

report_sex_differences(): Report sex differences

run_OSA(): Run the Ordinal SuStaIn Algorithm (OSA)

run_OSA_permuted(): Randomly permute some some variables and run the OSA model on the permuted data

run_and_save_OSA(): Run the Ordinal SuStaIn algorithm (OSA) or load results from presaved .rds file if available

run_app(): Run the Shiny Application

scid_vars_for_table1(): List SCID variables to display in data summary tables

search_articles(): Search PubMed for FXTAS-related articles

shared_flextable_settings(): Apply flextable settings to match Brain journal requirements

sim_data: Simulated data

sim_subtype_and_stage_table: Simulated subtype-and-stage table

stage_barplot(): Plot estimated stage counts

stage_barplot(<SuStaIn_model>): Plot estimated stage counts

stage_barplot(<default>): Plot estimated stage counts

stage_barplot(<list>): Plot estimated stage counts

stratified_formula(): Build a formula for table1::table1()

table1a(): table1::table1() with customized settings

table_subtype_by_demographics(): Create table of demographics statistics by most-likely latent subtype

test_data: Test Data

test_data_v1: Test Data - Visit 1

test_subtype_and_stage_table: Simulated subtype-and-stage table

write_permuted_test_stats(): Write permuted test stats as RDS