Contains various functions for optimal scaling. One function performs optimal scaling by maximizing an aspect (i.e. a target function such as the sum of eigenvalues, sum of squared correlations, squared multiple correlations, etc.) of the corresponding correlation matrix. Another function performs implements the LINEALS approach for optimal scaling by minimization of an aspect based on pairwise correlations and correlation ratios. The resulting correlation matrix and category scores can be used for further multivariate methods such as structural equation models.

Tools for the analysis and visualization of bilateral asymmetry in parasitic infections.

Perform one-dimensional spline regression with automatic knot selection.
      This package uses a penalized approach to select the most relevant knots.
      B-splines of any degree can be fitted. More details in 'Goepp et al. (2018)',
      "Spline Regression with Automatic Knot Selection", <arXiv:1808.01770>.

R codes for the (adaptive) Sum of Powered Score ('SPU' and 'aSPU')
    tests, inverse variance weighted Sum of Powered score ('SPUw' and 'aSPUw') tests
    and gene-based and some pathway based association tests (Pathway based Sum of
    Powered Score tests ('SPUpath'), adaptive 'SPUpath' ('aSPUpath') test, 'GEEaSPU'
    test for multiple traits - single 'SNP' (single nucleotide polymorphism)
    association in generalized estimation equations, 'MTaSPUs' test for multiple
    traits - single 'SNP' association with Genome Wide Association Studies ('GWAS')
    summary statistics, Gene-based Association Test that uses an extended 'Simes'
    procedure ('GATES'), Hybrid Set-based Test ('HYST') and extended version
    of 'GATES' test for pathway-based association testing ('GATES-Simes'). ).
    The tests can be used with genetic and other data sets with covariates. The
    response variable is binary or quantitative. Summary; (1) Single trait-'SNP' set
    association with individual-level data ('aSPU', 'aSPUw', 'aSPUr'), (2) Single trait-'SNP'
    set association with summary statistics ('aSPUs'), (3) Single trait-pathway
    association with individual-level data ('aSPUpath'), (4) Single trait-pathway
    association with summary statistics ('aSPUsPath'), (5) Multiple traits-single
    'SNP' association with individual-level data ('GEEaSPU'), (6) Multiple traits-
    single 'SNP' association with summary statistics ('MTaSPUs'), (7) Multiple traits-'SNP' set association with summary statistics('MTaSPUsSet'), (8) Multiple traits-pathway association with summary statistics('MTaSPUsSetPath').