Instrumental Variable Analysis in Case-Control Association
Studies
Mendelian randomization (MR) analysis is a special case of instrumental variable analysis with genetic instruments. It is used to estimate the unconfounded causal effect of an exposure. This package implements estimating and testing methods in Zhang et al. (2019) for MR analysis in case-control studies. It (1) estimates the causal effect of a quantitative exposure by the quasi empirical likelihood approach; (2) uses Lagrange multiplier test for testing the presence of causal; (3) provides a test for the presence of confounder.

c(person(given = "Mika", family = "Sipilä", role = c("aut", "cre"), email = "mika.e.sipila@student.jyu.fi"),
person(given = "Klaus", family = "Nordhausen", role = c("aut"),
comment = c(ORCID = "0000-0002-3758-8501")),
person(given = "Sara", family = "Taskinen", role = "aut",
comment = c(ORCID = "0000-0001-9470-7258")))
Independent vector analysis (IVA) is a blind source separation (BSS) model where several datasets are jointly unmixed. This package provides several methods for the unmixing together with some performance measures. For details, see Anderson et al. (2011) <doi:10.1109/TSP.2011.2181836> and Lee et al. (2007) <doi:10.1016/j.sigpro.2007.01.010>.
Mika Sipilä [aut, cre],
Klaus Nordhausen [aut] (<https://orcid.org/0000-0002-3758-8501>),
Sara Taskinen [aut] (<https://orcid.org/0000-0001-9470-7258>)

Bayesian Instrumental Variable Estimation and Model
Determination via Conditional Bayes Factors
Alex Lenkoski, Anna Karl, Andreas Neudecker
This package provices functions to estimate the parameters
for linear regression equations using gibbs sampling and
bayesian model averaging

This package allows one incorporate instrument and
covariate uncertainty into instrumental variable regression.

This package allows one incorporate instrument and covariate uncertainty into instrumental variable regression.

Profiling Compliers and Non-Compliers for Instrumental Variable
Analysis
Moritz Marbach <moritz.marbach@gess.ethz.ch> [aut, cre]
Estimating the mean and variance of a covariate for the complier, never-taker and always-taker subpopulation in the context of instrumental variable estimation. This package implements the method described in Marbach and Hangartner (2019) <doi:10.2139/ssrn.3380247>.