๐Ÿ”™ Home

Introduction

When youโ€™ve run your statistical models and gathered all the numbers, how do you report them in-line in your text? In this tutorial, I will show you which numbers are most commonly reported in academic prose (e.g., in articles), and what the conventions are for formatting them in-line. This is certainly not the only way to report your statistics, but it is how I have done so and what I most commonly have seen in the literature. Please feel free to send me feedback or comments if you think there is a better way to report any of these tests!

library(lme4,ordinal)
# Load in three data sets to try out
# 1) dataBin = binomial data from a simulated forced-choice task
# 2) dataOrd = ordinal rating data from a simulated Likert scale task
# 3) dataCon = continuous numeric data from a simulated reaction time task

dataBin <- read.csv("data/binomial-data.csv",header=TRUE, stringsAsFactors = TRUE)
head(dataBin)

The dataset Iโ€™m using here has a binomial dependent variable selection (which is coded as hits with 1s and misses with 0s in the column called selectCode`). This data frame was designed to mimic a forced-choice task, such as selecting which of two sentences sounds more natural. There are two levels of the primary independent variable:

levels(dataBin$condition)
[1] "Baseline"  "Treatment"

In this simulated data set, the same task was carried out in three different experiments, which are labled as below:

levels(dataBin$experiment)
[1] "first"  "second" "third" 

Finally, letโ€™s take a look at what our data look like. These graphs displays the selection of Options 1 and 2 by condition and experiment, and their interaction. This is not the only way to visualise this data, but it will be particularly helpful in the interpretation of interactions later on.

library(ggplot2)
ggplot(dataBin, aes(x=condition)) + geom_bar(aes(fill=selection),position="stack") + ggtitle("Selection across Condition only")