Melanie Colón Posted November 22, 2017 Share Posted November 22, 2017 Social Network Analysis for Behavioural Scientists using R (SNAR01)https://www.psstatistics.com/course/social-network-analysis-for-behavioral-scientists-snar01/Delivered by Prof. James Curley3rd July 2018 - 6th July 2018Please feel free to share this anywhere you feel is suitable.Course Overview:This workshop will provide students with the opportunity to learn how touse social network analysis to analyze social relational datasets such ashuman friendship networks or animal social networks. Attendees will learnhow to use R and several R packages including igraph, sna, network, asnipe,timeordered, tsna to create network graphs, calculate descriptive networkmetrics, use randomization and random models to evaluate the significanceof these metrics, determine graph structural properties including communitystructures, use QAP and MRQAP methods to assess how network characteristicsrelate to other individual and relational attributes, and measure changeover time in dynamic networks. Attendees will also learn how to producehigh quality network visualizations using R.Monday 2nd – Classes from 09:00 to 17:00Elementary concepts.Module 1: Introduction to Social Networks Theory. This will cover centralthemes of social network analysis: the major data formats, structures andcollection methods, the different types of graphs and networks; how togenerate and visualize social networks and generate basic descriptivestatistics, and what hypotheses and questions can be addressed using socialnetwork analysis. We will also discuss data types and questions of interestto attendees.Module 2: R refresher and R packages. This module will provide a quickoverview of the major packages used for social network analysis in Rincluding ‘igraph’, ‘sna’, ‘network’. We shall learn how to convert rawdata formats to network objects in R; how to interface with R networkobjects and how to create simple network visualizations.Module 3: Intro to Visualizing Networks. We shall cover how to generate andbeautify networks using the ‘igraph’ R package covering issues such aslayout decisions, coloring and sizing of nodes and edges by networkattributes, metrics or community. We shall extend this to cover how tocreate dynamic three-dimentional network plots using the Rpackage ‘threejs’. We shall also discuss how to use the ‘ggplot’based ‘ggraph’ R package which has many customizable features for plottingnetworks.Tuesday 3rd – Classes from 09:00 to 17:00Basic analyses.Module 4: Identifying important nodes and edges. Learn how to evaluate keyindicators of each node’s significance to the network including, degreecentrality, eigenvector centrality, power centrality, and betweenness.Describe how to calculate for directed vs. undirected and weighted vsunweighted networks. Learn how to assess simple relationships between nodesincluding geodesic distances, identifying neighbors, determining shortestand longest paths.Module 5: Introduction to Network Randomization and Random Models. It iscritical in network analysis to evaluate how likely it is to observe agiven network metric for our network of interest. This module willintroduce how to use null models (randomizations/permutations or randomgraphs) to test whether networks have characteristics that are especiallysurprising after accounting for non-independence. We also will learn how togenerate confidence intervals for network metrics and carry outsignificance testing. We shall learn how to use the ‘igraph’ package forrandom graph generation.Module 6: Network Graph Characteristics. We shall cover concepts such asdyad and triad censuses, transitivity, assortativity, homophily,reciprocity, clustering and density. We shall discuss their significanceand importance for answering relevant questions to the patterns of socialassociations and behavior in networks.Wednesday 4th – Classes from 09:00 to 17:00Extending Network Analysis.Module 7: Community Detection. Overview of what communities (modules) meanfor animal and human social networks – that a high proportion of nodes oredge weights cluster within a sub-group of nodes/edges rather than betweensub-groups. We shall review the numerous community detection methods anddescribe the implementation of major ones in R. How to generate robustnessin evaluation of community detection. How to to determine the degree ofcommunity structure in a network using the index of modularity (Q) andbootstrapping techniques such as community assortativity (rcom).Hierarchical clustering for analysis of hierarchically organized socialsocieties.Module 8: Randomizations and Random models II. This module will furtherexplore how to determine the appropriate choice of null models forbehavioral data. This is not always a trivial exercise for behavioraldatasets. We will use the ‘asnipe’ R package for network permutationand ‘igraph’ R package for null model generation. We shall also coveroptions for dealing with missing data, low sampling rates and pseudo-replication, options for data imputation, and how to account for temporalstructure in data randomizations.Thursday 5th – Classes from 09:00 to 17:00Advanced Methods.Module 9: Quadratic Assignment Procedure (QAP) Regression. Using QAPregression to control for non-independence of data when comparing networkposition or strength between networks or comparing individual/dyadicnetwork metrics with other individual/dyadic attributes. Extending analysesto using multiple regression quadratic assignment procedure (MRQAP). How toperform in base-R and using the ‘asnipe’ R package. How to generate effectsizes when using QAP and MRQAP.Module 10: Visualizing Networks II. This module will tackle advancedoptions for network plotting, including how to export ‘igraph’ R objects toGephi for generating even more beautiful customized plots, how to createinteractive web based network visualizations using R packages suchas ‘threejs’, ‘visNetwork’ and ‘networkD3’, and how to plot or animatedynamic social networks.Module 11: Dynamic Networks. Key questions that are often neglected are howdo network structures remain stable or change over time and can we inferhow meaningful this stability and instability is? This module will discussvarious methods for analysis of change for time-ordered and time-aggregatednetworks. We will use R packages for analysis of dynamic networksincluding ‘timeordered’, ‘networkDynamic’ and ‘tsna’.Send inquiries to oliverhooker@psstatistics.com1. November 27th – December 1st 2017INTRODUCTION TO PYTHON FOR BIOLOGISTS #IPYBMargam Discovery Centre, Wales, Dr. Martin Joneshttp://www.prinformatics.com/course/introduction-to-python-for-biologists-ipyb04/--------------------------------------------------------------------------------------------------------------------------------------------------------------------------2. December 4th - 8th 2017ADVANCING IN STATISTICAL MODELLING USING R #ADVRMargam Discovery Centre, Wales, Dr. Luc Bussiere, Dr. Tom Houslay, Dr. AneTimenes Laugen,http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr07/--------------------------------------------------------------------------------------------------------------------------------------------------------------------------3. January 29t – February 2nd 2018INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING #IBHMSCENE, Scotland, Dr. Andrew Parnellhttp://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/4. January 29th – February 2nd 2018PHYLOGENETIC DATA ANALYSIS USING R #PHYLSCENE, Scotland, Dr. Emmanuel Paradishttps://www.prstatistics.com/course/introduction-to-phylogenetic-analysis-with-r-phyg-phyl02/--------------------------------------------------------------------------------------------------------------------------------------------------------------------------5. February 19th – 23rd 2018MOVEMENT ECOLOGY #MOVEMargam Discovery Centre, Wales, Dr Luca Borger, Dr Ronny Wilson, DrJonathan Pottshttps://www.prstatistics.com/course/movement-ecology-move01/6. February 19th – 23rd 2018GEOMETRIC MORPHOMETRICS USING R #GMMRMargam Discovery Centre, Wales, Prof. Dean Adams, Prof. Michael Collyer,Dr. Antigoni Kaliontzopoulouhttp://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/--------------------------------------------------------------------------------------------------------------------------------------------------------------------------7. March 5th - 9th 2018SPATIAL PRIORITIZATION USING MARXAN #MRXNMargam Discovery Centre, Wales, Jennifer McGowanhttps://www.prstatistics.com/course/introduction-to-marxan-mrxn01/8. March 12th - 16th 2018ECOLOGICAL NICHE MODELLING USING R #ENMRGlasgow, Scotland, Dr. Neftali Sillerohttp://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr02/9. March 19th – 23rd 2018BEHAVIOURAL DATA ANALYSIS USING MAXIMUM LIKLIHOOD IN R #BDMLGlasgow, Scotland, Dr William Hoppitthttp://www.psstatistics.com/course/behavioural-data-analysis-using-maximum-likelihood-bdml01/--------------------------------------------------------------------------------------------------------------------------------------------------------------------------10. April 9th – 13th 2018NETWORK ANAYLSIS FOR ECOLOGISTS USING R #NTWAGlasgow, Scotland, Dr. Marco Scottihttps://www.prstatistics.com/course/network-analysis-ecologists-ntwa02/11. April 16th – 20th 2018INTRODUCTION TO STATISTICAL MODELLING FOR PSYCHOLOGISTS USING R #IPSYGlasgow, Scotland, Dr. Dale Barr, Dr Luc Bussierrehttp://www.psstatistics.com/course/introduction-to-statistics-using-r-for-psychologists-ipsy01/12. April 23rd – 27th 2018MULTIVARIATE ANALYSIS OF ECOLOGICAL COMMUNITIES USING THE VEGAN PACKAGE#VGNRGlasgow, Scotland, Dr. Peter Solymos, Dr. Guillaume Blanchethttps://www.prstatistics.com/course/multivariate-analysis-of-ecological-communities-in-r-with-the-vegan-package-vgnr01/13. April 30th – 4th May 2018QUANTITATIVE GEOGRAPHIC ECOLOGY: MODELING GENOMES, NICHES, AND COMMUNITIES#QGERGlasgow, Scotland, Dr. Dan Warren, Dr. Matt Fitzpatrickhttps://www.prstatistics.com/course/quantitative-geographic-ecology-using-r-modelling-genomes-niches-and-communities-qger01/--------------------------------------------------------------------------------------------------------------------------------------------------------------------------14. May 7th – 11th 2018 ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIALECOLOGICAL DATA USING R #MVSPCANADA (QUEBEC), Prof. Pierre Legendre, Dr. Guillaume Blanchethttps://www.prstatistics.com/course/advances-in-spatial-analysis-of-multivariate-ecological-data-theory-and-practice-mvsp03/15. May 14th - 18th 2018INTRODUCTION TO MIXED (HIERARCHICAL) MODELS FOR BIOLOGISTS #IMBRCANADA (QUEBEC), Prof Subhash Lelehttps://www.prstatistics.com/course/introduction-to-mixed-hierarchical-models-for-biologists-using-r-imbr01/16. May 21st - 25th 2018INTRODUCTION TO PYTHON FOR BIOLOGISTS #IPYBSCENE, Scotland, Dr. Martin Joneshttp://www.prinformatics.com/course/introduction-to-python-for-biologists-ipyb05/17. May 21st - 25th 2018INTRODUCTION TO REMOTE SENISNG AND GIS FOR ECOLOGICAL APPLICATIONSGlasgow, Scotland, Prof. Duccio Rocchini, Dr. Luca Delucchihttps://www.prinformatics.com/course/introduction-to-remote-sensing-and-gis-for-ecological-applications-irms01/18. May 28th – 31st 2018STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR #SIMMCANADA (QUEBEC) Dr. Andrew Parnell, Dr. Andrew Jacksonhttps://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm04/19. May 28th – June 1st 2018ADVANCED PYTHON FOR BIOLOGISTS #APYBSCENE, Scotland, Dr. Martin Joneshttps://www.prinformatics.com/course/advanced-python-biologists-apyb02/--------------------------------------------------------------------------------------------------------------------------------------------------------------------------20. June 12th -0 15th 2018SPECIES DISTRIBUTION MODELLING #DBMRMyuna Bay sport and recreation, Australia, TBCCOMING SOON www.PRstatistics.com21. November 6th – 10th 2017LANDSCAPE GENETIC DATA ANALYSIS USING R #LNDGMyuna Bay sport and recreation, Australia, TBCCOMING SOON www.PRstatistics.com22. June 18th – 22nd 2018STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTSUSING R #SEMRMyuna Bay sport and recreation, Australia, TBCCOMING SOON www.PRstatistics.com--------------------------------------------------------------------------------------------------------------------------------------------------------------------------23. July 2nd - 5th 2018SOCIAL NETWORK ANALYSIS FOR BEHAVIOURAL SCIENTISTS USING R #SNARGlasgow, Scotland, Prof James Curleyhttp://www.psstatistics.com/course/social-network-analysis-for-behavioral-scientists-snar01/24. July 8th – 12th 2018MODEL BASE MULTIVARIATE ANALYSIS OF ABUNDANCE DATA USING R #MBMVGlasgow, Scotland, Prof David Wartonhttps://www.prstatistics.com/course/model-base-multivariate-analysis-of-abundance-data-using-r-mbmv02/25. July 16th – 20th 2018PRECISION MEDICINE BIOINFORMATICS: FROM RAW GENOME AND TRANSCRIPTOME DATATO CLINICAL INTERPRETATION #PMBIGlasgow, Scotland, Dr Malachi Griffith, Dr. Obi Griffithhttps://www.prinformatics.com/course/precision-medicine-bioinformatics-from-raw-genome-and-transcriptome-data-to-clinical-interpretation-pmbi01/26. July 23rd – 27th 2018EUKARYOTIC METABARCODINGGlasgow, Scotland, Dr. Owen Wangensteenhttp://www.prinformatics.com/course/eukaryotic-metabarcoding-eukb01/-------------------------------------------------------------------------------------------------------------------------------------------------------- Link to comment Share on other sites More sharing options...
Recommended Posts
Archived
This topic is now archived and is closed to further replies.