Diagnostics and data preparation for random effects within estimator, random effects within-idiosyncratic estimator, between-within-idiosyncratic model, and cross-classified between model. Mundlak, Yair (1978) <doi:10.2307/1913646>. Hausman, Jeffrey (1978) <doi:10.2307/1913827>. Allison, Paul (2009) <doi:10.4135/9781412993869>. Neuhaus, J.M., and J. D. Kalbfleisch (1998) <doi:10.2307/3109770>.

This package contains various tools to perform and visualize Response Item Networks ('ResIN's'). ResIN dummy-codes ordered and qualitative response choices from (survey) data, calculates pairwise associations and maps the location of each item response as a node in a force-directed network. Please refer to <https://www.resinmethod.net/> for more details.

The Ryan-Holm step-down Bonferroni or Sidak procedure is to control the family-wise (experiment-wise) type I error rate in the multiple comparisons. This procedure provides the adjusting p-values and adjusting CIs. The methods used in this package are referenced from John Ludbrook (2000) <doi:10.1046/j.1440-1681.2000.03223.x>.

BM25 is a ranking function used by search engines to rank matching documents according to their relevance to a user's search query. This package provides a light wrapper around the BM25 rust crate for Okapi BM25 text search. For more information, see Robertson et al. (1994) <https://trec.nist.gov/pubs/trec3/t3_proceedings.html>.

The purpose of this GO.db annotation package is to provide detailed information about the latest version of the Gene Ontologies.

This package provides helper functions with a consistent interface to coerce and verify the types and shapes of values for input checking.

This package provides a derivative-free optimization by quadratic approximation based on an interface to Fortran implementations by M. J. D. Powell.

This package implements functions for multi-class discriminant analysis using binary predictors, for corresponding variable selection, and for dichotomizing continuous data.

These data contain morphological image measurements for dried beans from Koklu and Ozkan (2020) <doi:10.1016/j.compag.2020.105507>.

This package provides a Natural Language Processing Model trained to detect directness and intensity during conflict. See <https://www.mikeyeomans.info>.

Scripting of structural equation models via lavaan for Dyadic Data Analysis, and helper functions for supplemental calculations, tabling, and model visualization.

Bayesian estimation of forced choice models in Item Response Theory using rstan (See Stan Development Team (2020) <https://mc-stan.org/>).

Multivariate time series analysis based on Generalized Space-Time Autoregressive Model by Ruchjana et al.(2012) <doi:10.1063/1.4724118>.

Encode and decode the Google Encoded Polyline Algorithm Format. See <https://developers.google.com/maps/documentation/utilities/polylinealgorithm> for more information.

Hierarchical Bayesian models. The package provides tools to fit two response time models, using the population-based Markov Chain Monte Carlo.

This package provides a collection of palettes and themes for ggplot2', offering a light, pastel aesthetic. Syntax follows the viridis package.

Targeted Maximum Likelihood Estimation ('TMLE') of treatment/censoring specific mean outcome or marginal structural model for point-treatment and longitudinal data.

Maximum likelihood estimation of log-binomial regression with special functionality when the MLE is on the boundary of the parameter space.

Generates multivariate imputations using sequential regression with L2 penalty. For more details see Zahid and Heumann (2018) <doi:10.1177/0962280218755574>.

This GUI for the mi package walks the user through the steps of multiple imputation and the analysis of completed data.

This package implements the MVOPR (Multi-View Orthogonal Projection Regression) method for robust variable selection and integration of multi-modality data.

Create vectors with sticky flags for elements that should not be displayed. Numeric vectors have basic subset and arithmetic methods implemented.

Connects to Google cloud vision <https://cloud.google.com/vision> to perform label detection and repurpose this feature for image classification.

This package provides a native R client library for querying the Prometheus time-series database, using the PromQL query language.