How many types of statistical analysis approaches do you use regularly

Whilst deciphering  really cool R package called GDM (see below), I was thinking about how many different statistical approaches and techniques have have I read about, deciphered and applied in the last 2 years?  What’s a usual number of techniques people use reasonably regularly? My list is at approximately 30 currently –  but I am a postdoc that spends basically all of my time analyzing data from diverse range of systems with an equally wide variety of data types, so  perhaps that’s normal?

The first place I started looking was in my R package list and I quickly realized that there were quite a few. I excluded ‘bread and butter’ GLM type analyses and there Bayesian equivalents e.g., ANOVA & GLMMs and basic ordination techniques (e.g., PCoA, NMDS). I  haven’t also included techniques to calculate the various aspects of diversity or sequence alignment algorithms either as the list would just keep going. As I deal with species distribution data,  distances and (dis)similarities quite often there was obviously a trend towards distance-based techniques (see below), with a mixture of spatial, epi and phylogenetic approaches.

I’m too lazy to add citations and descriptions for each one – but they are all easy to find in google or email me if you are interested. If there is anything else that I should know and use to answer disease/phylogenetic community ecology type questions, please make suggestions.

In no particular order:

Permutation-based ANOVA (PERMANOVA), permutation based tests for homogeneity of dispersion PERMDISP, canonical analysis of principal coordinates (CAP) analyses , dbMEMs, Generalized dissimilarity modelling (GDM), distance-based linear modelling (distLM), multiple matrix regression (MRM), network-based linear models (netLM), Gradient Forests, Random Forests, cluster analysis, SYNCSA analysis,  fourth corner analysis, RLQ tests, Mantel tests, Moran’s I tests (phylogenetic and spatial), Phylogenetic GLMMs, everything in the R package Picante, ecophylogenetic regression (Pez), dynamic assembly model of colonization, local extinction and speciation (DAMOCLES), dynamical assembly of islands by speciation, immigration and extinction (DAISIE), all sorts of ancestral state reconstruction approaches, numerous Bayesian evolutionary analysis sampling trees (BEAST) methods, numerous phytools methods, environmental raster and phylogenetically informed movement (SERAPHIM),SaTScan, Circuitscape, point-time pattern analysis, Kriging, epitools risk analysis.

Link to GDM: https://cran.r-project.org/web/packages/gdm/vignettes/gdmVignette.pdf

 

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