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Recent Posts
 Getting started — loading data, writing and saving scripts January 16, 2014
 Getting started – getting helped January 16, 2014
 Getting started — Installation of RStudio and some packages + using ggplot() to make a simple plot January 16, 2014
 Postgraduate data analysis and interpretation January 16, 2014
 Mixedeffects modeling — four hour workshop — part IV: LMEs November 5, 2013
Tag Archives: regression
Modelling – mixed effects – concepts
I am going to take another shot at considering mixed effects modelling. This time from a perspective closer to my starting point. I first learnt about mixedeffects modelling through reading about it in, I think, some paper or chapter by … Continue reading
Posted in 16. Modelling  mixedeffects
Tagged anova(), F', lmer(), minF', mixed effects, mixede, regression
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Modelling – ordinary least squares regression
Let’s work on our understanding of regression while we work through some examples. We have two datasets to work with, one on the attributes of the participants of a lexical decision study (their age, reading skill etc.), and one on … Continue reading
Modelling – ordinary least squares regression in R
We will be looking at how you can do regression in R. More than one function call will do this, lm() and ols() in R. Don’t ask me why, I might find out another time. Ordinary least squares regression: — … Continue reading
Modelling – some conceptual foundations
We have discussed the relationships between pairs of variables, we will now move on to analyzing our data using linear regression. Slides on regression can be downloaded here. You will see in those slides that I rely very heavily on … Continue reading
Modelling – next steps
Having dwelt on the relationships between pairs of variables, both in terms of scatterplot depictions and, lately, in terms of correlations, we can move on to the real core of our focus in analyzing psycholinguistic data: linear regression. Creative commons … Continue reading
Modelling – examining the correlations between predictor variables
This post will consider how to explore the relationship between a set of variables: variables that we will ultimately use in a mixedeffects analysis of lexical decision data. Most of the analyses we will be doing will examine whether observed … Continue reading
Posted in 10. Modelling  collinearity, modelling, rstats
Tagged collinearity, correlation, multicollinearity, regression
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Getting started – drawing a scatterplot, with a linear regression smoother, edited title, label and theme, for report
This post assumes that you have installed and are able to load the ggplot2 package, that you have been able to download the ML subject scores database and can read it in to have it available as a dataframe in … Continue reading →