Title: Inverse Probability Weighted Estimation of Average Treatment
Effect with Misclassified Binary Outcome
Description: An implementation of the correction methods proposed by Shu and Yi (2017) <doi:10.1177/0962280217743777> for the inverse probability weighted (IPW) estimation of average treatment effect (ATE) with misclassified binary outcomes. Logistic regression model is assumed for treatment model for all implemented correction methods, and is assumed for the outcome model for the implemented doubly robust correction method. Misclassification probability given a true value of the outcome is assumed to be the same for all individuals.

Title: Protein Quantification in Mass Spectrometry-Based Proteomics
person("Alex", "Henneman", email = "a.henneman@amsterdamumc.nl",
Description: An implementation of the maximal
peptide ratio extraction module of the MaxLFQ algorithm by
pipeline for processing proteomics data in data-independent acquisition mode.
It offers additional options for protein quantification using the N most intense
fragment ions, and a wrapper for the median polish algorithm by Tukey (1977, ISBN:0201076160).

pipeline for processing proteomics data in data-independent acquisition mode
(Pham et al. 2020 <doi:10.1093/bioinformatics/btz961>).

It offers additional options for protein quantification using
the N most intense fragment ions, using all fragment ions, and
a wrapper for the median polish algorithm by Tukey (1977, ISBN:0201076160).

Description: An implementation of the MaxLFQ algorithm by
Cox et al. (2014) <doi:10.1074/mcp.M113.031591> in a comprehensive
In general, the tool can be used to integrate multiple
proportional observations into a single quantitative value.

Author: Kristin A. Linn, Eric B. Laber, Leonard A. Stefanski
Maintainer: Kristin A. Linn <kalinn@ncsu.edu>
Description: Estimate an optimal dynamic treatment regime using Interactive Q-learning

Description: Estimate an optimal dynamic treatment regime using Interactive Q-learning.

Maintainer: Kristin A. Linn <klinn@pennmedicine.upenn.edu>