Introduction to statistical modelling for psychologists in R (IPSY01)

https://www.psstatistics.com/course/introduction-to-statistics-using-r-for-psychologists-ipsy01/

This course will be delivered by Dr Dale Barr and Dr Luc Bussiere and will run from the 16th - 20th April 2018 in Scotland.

Course Overview:
This course will provide an introduction to working with real-life data typical of those encountered in the field of psychology. The course will be delivered by Dr. Dale Barr and Dr. Luc Bussière, who are practicing academics in the fields of psychology and evolutionary biology respectively, with many years of expertise with R and statistical modelling as both scientists and instructors.  This five-day course will consist of series of modules (each lasting roughly half a day) covering topics including the basic ‘canon’ of psychological statistics (t-test, correlation/regression, ANOVA) presented within the framework of general linear models, and building up to logistic regression and linear mixed-effects modelling. Along the way you will gain in-depth experience in data wrangling using the R ‘tidyverse’, data and model visualisation and plotting, as well as exploring and understanding model diagnostics. Classes will consist of a mixture of lectures and practical exercises designed to either build required skills for future modules or to perform a family of analyses that is frequently encountered in the psychological literature.

Monday 16th
Introduction to R/RStudio
• interacting with the RStudio IDE
• installing add-on packages
• R scripts and R notebooks
• coding style guidelines
• session management and project organization
Data wrangling and reproducible workflows with the tidyverse
• loading datasets (csv, excel, SPSS, google drive)
• filtering, sorting, and reshaping data
• grouping and summarizing data
• combining datasets using joins
• chaining commands together using ‘pipes’

Tuesday 17th
Data visualization with ggplot2
• the ‘grammar of graphics’ philosophy
• univariate plots: histograms, density plots, boxplots, bar graphs, violin and pirate plots
• bivariate plots: scatterplots, line graphs, interaction plots
• enhancing plots using labels and themes
• creating subplots with faceting

The psychology stats ‘canon’ and the General Linear Model
• t-tests, confidence intervals, effect size, and power
• correlation matrices and simple linear regression
• contingency tables; chi-square tests
• correlation and simple regression

Wednesday 18th
Multiple Regression
• coding categorical predictors
• detecting and dealing with multicollinearity
• polynomial models for time-series data
• model comparison and information criteria
• model checking/validation, plotting predictions

Thursday 19th
Analysis of Variance in the GLM framework
• one-factor designs
• multifactor designs: main effects and interactions
• within-subject and mixed designs
• checking assumptions (sphericity, normality, homogeneity of variance)
• plotting and interpreting interactions
• follow-up tests and contrasts

Generalized Linear Models
• binary data (logistic regression)
• count data (Poisson regression)
• generating and plotting model predictions

Friday 20th
Introduction to Linear Mixed-Effects Models
• crossed random effects of participant and item
• understanding variance components through data simulation
• specifying the random effects structure
• translating study design into lmer model syntax

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Other upcoming courses include

Introduction to Bayesian hierarchical modelling using R (IBHM02) 
https://www.psstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/

Behavioural data analysis using maximum likelihood in R (BDML01) 
https://www.psstatistics.com/course/behavioural-data-analysis-using-maximum-likelihood-bdml01/

Introduction to statistical modelling for psychologists in R (IPSY01) 
https://www.psstatistics.com/course/introduction-to-statistics-using-r-for-psychologists-ipsy01/

Social Network Analysis for Behavioural Scientists using R (SNAR01) 
https://www.psstatistics.com/course/social-network-analysis-for-behavioral-scientists-snar01/

Also check out our courses at www.PRstatisrtics.copm and www.PRinformatics.com

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