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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
Category Archives: rstats
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
Getting started – revision of dataframe input, new on looking at data type
This post assumes that you have read and worked through examples in previous posts concerning: 1. how to read in .csv files as dataframes; 2. data structure basics, including discussion of vectors, matrices, and dataframes. We will be working with … Continue reading
Posted in 8. Getting started  data, getting started, rstats
Tagged as.factor, as.numeric, coercion, dataframe, is.factor, is.numeric, variable
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Modelling – examining correlations among predictors
In a previous post, we used merge() to create a joint database holding a large set of data on the attributes of the 160 words presented in a lexical decision experiment whose completion I supervised a while ago. I would … Continue reading
Modelling – examination correlations: advanced scatterplots
This post will focus exclusively on the relationships between pairs of variables. We will be looking at the item norms data, though you might want to practice the R procedures we deploy on the subjects data (see earlier posts here, … Continue reading
Posted in 12. Modelling  scatterplots+, modelling, rstats
Tagged correlation, scatterplot
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Modelling – examining correlations: first, look at predictor distributions
This post follows on from the previous post, concerning the examination of variable distributions. It is always useful to plot the distribution of variables like item attributes e.g. item length in letters. One important benefit of doing so is identifying … Continue reading
Posted in 11. Modelling  distributions, modelling, rstats
Tagged describeBy, statistics, summary, ttest
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Modelling – examining correlations: first, look at predictor distributions
This post will take a more indepth look at the relationships between variables. A key property of experimental data is that we measure attributes – characteristics of people, stimuli, and behaviour – and that those measurements (the numbers) vary. Numbers … Continue reading
Posted in 11. Modelling  distributions, modelling, plotting data, rstats
Tagged density, distribution, grid, histogram, pdf, ttest
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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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