Package index • subtyper

All functions
`VarSelLCMproba.post()`	Bug fix to predict function in the VarSelLCM package
`adjustByCovariates()`	Covariate adjustment
`adjustByCovariatesUni()`	Covariate adjustment for many variables based on a single variable
`adjust_p_values()`	Adjust P-values and Return Subsetted Dataframe
`analyze_longitudinal_change()`	Analyze and Visualize Longitudinal Change with a Mixed-Effects Model
`asam()`	Compute ASymmetry-Adjusted Mean (ASAM) for Asymmetry Analysis
`assembleTestRetest()`	Find test-retest data within a dataframe
`assign_qc_ratings_NM2DMT()`	Assign Quality Control Ratings Based on Specific Criteria
`asymind()`	Asymmetry index for asymmetry analysis
`asymmetry()`	Compute Various Asymmetry Metrics Between Two Sides
`augment_with_custom_color()`	Augment a Data Frame with Custom Color Column
`averageRepeats()`	Average repeat data
`balanceDataMultiClass()`	balanced sampling of a multi-class variable
`balancedDataframe()`	balanced sampling of a variable
`biclusterMatrixFactorization()`	Matrix factorization biclustering
`bipartite_variable_match()`	Bipartite Variable Match
`clearcolname()`	clearcolname
`collect_and_zip_images()`	Collect and Zip Images Based on Subject-Date List
`combat_with_na()`	Apply ComBat Batch Correction While Preserving Missing Data
`compare_model_predictions()`	Compare Model Predictions with True Values
`complete_cases_from_equation()`	Extract Complete Cases from a Data Frame Based on a Model Equation
`consensusSubtypingCOCA()`	consensusSubtypingCOCA
`consensusSubtypingPAM()`	consensusSubtypingPAM
`consensusSubtypingPredict()`	consensusSubtypingPredict
`consensusSubtypingPrep()`	consensusSubtypingPrep
`consensusSubtypingTrain()`	consensusSubtypingTrain
`convert_to_random_effects()`	Convert Character Vector to Random Effects Terms for lme4
`count_unique_subjects_per_diagnosis()`	Count Unique Subjects per Diagnosis
`create_radar_chart()`	Create a Radar Chart
`create_table1()`	Create a Publication-Ready Summary Table (Table 1)
`dataPartition()`	balanced data partition
`dcurvarsel()`	dcurvarsel
`eliminateNonUniqueColumns()`	Eliminate Non-Unique Columns from a Matrix
`featureImportanceForSubtypes()`	subtype feature importance
`fill1col2another()`	fill1col2another
`fillBaselineColumn()`	fill baseline column
`filterByVisit()`	Get subjects within a given set of visits
`filterForGoodData()`	Uses outlierness scoring to filter a data frame
`filterNAcolumns()`	Filter Columns by Percentage of NA Values
`find_closest_subjects()`	Find Closest Subjects
`force_unload_package()`	Forcefully Unload a Package in R
`fs()`	Convert NA to false
`generateSubtyperData()`	Generate example data for illustrating `subtyper`
`getExt()`	Get the file extension from a file-name. from `reader` package.
`getNamesFromDataframe()`	Extract column names with concatenated search parameters
`grepl_multi()`	Multi-pattern Matching in Character Vectors
`harmonize_sites()`	Harmonize Multiple Features Across Sites with Progress Indicator
`harmonize_sites_quantiles()`	Harmonize Multiple Features Across Sites with Quantile Matching
`hierarchicalSubtypePlots()`	subtype plotting
`highestQualityRepeat()`	Get subjects and timepoints with the best quality
`identify_best_voi()`	Identify Best Variable of Interest (VOI)
`interpret_icc()`	Interpret ICC Value
`kable_table()`	Create a Styled LaTeX Table with Adjustable Size and Orientation
`lm_anv_p_and_d()`	Linear Regression Analysis with ANOVA and Effect Size Calculation
`lmer_anv_p_and_d()`	Fit and compare linear mixed-effects models and calculate effect sizes.
`lmer_anv_p_and_d_old()`	Linear Mixed Effects Model Analysis with ANOVA and Effect Size Calculation
`log_parameters()`	Log Parameters of a Function Call
`mapAsymVar()`	Convert left/right variables to a measure of asymmetry
`mapLRAverageVar()`	Convert left/right variables to an average measurement
`matchVectorDistributionByQuantiles()`	Match a pair of vector distributions based on quantiles
`match_cohort_pair()`	Minimize the difference between two data frames based on t-statistic.
`match_data_frames()`	Match Data Frames Using Greedy K-Nearest Neighbors
`merge_ADNI_antspymm_by_closest_date()`	Process Clinical/Demographic and imaging Data for an ADNI Study
`merge_ppmi_imaging_clinical_demographic_data()`	Process Clinical/Demographic and imaging Data for a PPMI Study
`mlr3classification()`	mlr3classifier
`mlr3classifiercv()`	mlr3classifiercv
`mlr3classifiers()`	mlr3classifiers
`multigrep()`	Grep entries with a vector search parameters
`na2f()`	Convert NA to false
`nallspdma`	nallspdma
`normativeSummary()`	Normative Summary
`nrgDateToRDate()`	Convert nrg format date to R format date
`outlierness()`	Outlierness scoring
`oversample_minority()`	Oversample a minority class in a data frame
`plinkVariantsDataFrame()`	genetic variants data frame from plink data
`plotCategoricalData()`	Plot Categorical Data
`plotSubtypeChange()`	Plot longitudinal trajectories across subtypes
`plot_regression_graph()`	Plot Regression Results as a Graph
`predictSubtypeClusterMulti()`	Predict subtype from multivariate data
`predictSubtypeUni()`	Predict subtype for univariate data
`prplot()`	prplot
`quantSquared()`	quantify by quantiles (quantSquared)
`rank_results()`	Rank Rows Based on Weighted Scores of Specified Columns
`regressionBasedFeatureSelection()`	select top features via linear regression on an outcome
`rejectLowestQualityRepeat()`	Reject subjects and timepoints with lowest quality
`rename_columns()`	Rename Columns in a Data Frame
`reorderingDataframe()`	Reorder a subtype variable based on an external reference vector
`replaceName()`	Carefully replace a column name with a new one
`replace_values()`	Replace Values in a Vector
`replace_values_by_key()`	Replace Multiple Columns in Dataframe Based on a Matching Key
`rowwise_linear_variable_adjustments()`	Row-wise linear adjustments to variables in a dataframe
`run_association_analysis()`	A management function to run association analyses (LM or LMER) with progress.
`scale_variables_in_equation()`	Scale Numeric Variables in a Data Frame
`select_high_quality_data()`	Select High-Quality Imaging Data Based on Available QC Metrics
`select_important_variables()`	Select important variables based on stabilized correlations
`select_longitudinal_subjects()`	Select Longitudinal Subjects
`setSeedBasedOnTime()`	Set Seed Based on Current Time
`shorten_names()`	Shorten Names
`sinkhorn_method()`	Apply Sinkhorn method to stabilize a correlation matrix
`subset_multiple_visits()`	Subset Dataframe for Subjects with Multiple Unique Visits
`table_1()`	Generate a "Table 1" style summary for academic papers (Base R only).
`table_1_from_formula()`	Generate a table summarizing the data in a linear model formula.
`table_1_presentation()`	Format a table for publication using LaTeX or html
`threewayinteraction()`	three way interaction plot from raw data
`topk()`	Select Top k Rows Based on a Criterion
`trainSubtypeClusterMulti()`	Train subtype for multivariate data
`trainSubtypeUni()`	Train subtype for univariate data
`truncatehi()`	Truncate or Remove High Values
`undersample_majority()`	Undersample a majority class in a data frame
`visglm()`	Visualize the Joint Effect of Variables in a GLM
`visualize_timepoints()`	Visualize Longitudinal Data Across Time Points with Group Comparison

Reference

All functions