Estimating and Testing Intergenerational Social Mobility Effect
Estimate and test inter-generational social mobility effect on an outcome with cross-sectional or longitudinal data.

survey, gee, dplyr, lme4, stringr, parameters

Bayesian Analysis of Multivariate Counts Data in DNA
Metabarcoding and Ecology
Poisson-lognormal generalized linear mixed model analysis of multivariate counts data using MCMC, aiming to infer the changes in relative proportions of individual variables. The package was originally designed for sequence-based analysis of microbial communities ("metabarcoding", variables = operational taxonomic units, OTUs), but can be used for other types of multivariate counts, such as in ecological applications (variables = species). The results are summarized and plotted using 'ggplot2' functions. Includes functions to remove sample and variable outliers and reformat counts into normalized log-transformed values for correlation and principal component/coordinate analysis. Walkthrough and examples: http://www.bio.utexas.edu/research/matz_lab/matzlab/Methods_files/walkthroughExample_mcmcOTU_R.txt.

Bayesian analysis of multivariate counts data
This package implements poisson-lognormal generalized linear mixed model analysis of multivariate counts data using MCMC, aiming to infer the changes in relative proportions of individual variables. The package was originally designed for sequence-based analysis of microbial communities ("metabarcoding", variables = operational taxonomic units, OTUs), but can be used for other types of multivariate counts, such as in ecological applications (variables = species). The results are summarized and plotted using ggplot2 functions. Includes functions to remove sample and variable outliers and reformat counts into normalized log-transformed values for correlation and principal component/coordinate analysis. Walkthrough and examples: http://www.bio.utexas.edu/research/matz_lab/matzlab/Methods_files/walkthroughExample_mcmcOTU_R.txt

This package implements generalized linear mixed model analysis of qRT-PCR data based on lognormal-Poisson model fitted using MCMC. Also implemented are the lognormal model for higher-abundance data and a "classic" model involving multi-gene normalization. Several plotting functions are included to extract and visualize results. Tutorial: http://www.bio.utexas.edu/research/matz_lab/matzlab/Methods_files/mcmc.qpcr.tutorial.release1.pdf