Difference between revisions of "R Analysis"
(6 intermediate revisions by the same user not shown) | |||
Line 33: | Line 33: | ||
====[[R organizing data#prep stuff: data sets & making a new script|prep stuff: data sets & making a new script]]==== | ====[[R organizing data#prep stuff: data sets & making a new script|prep stuff: data sets & making a new script]]==== | ||
First download the following data sets, and unzip them to a local folder: | First download the following data sets, and unzip them to a local folder: | ||
*[http://weblab1.psych.ubc.ca/wikiakje/uploads/akwikishr/attentional_blink_data_set.zip attentional_blink_data_set.zip] | <!-- *[http://weblab1.psych.ubc.ca/wikiakje/uploads/akwikishr/attentional_blink_data_set.zip attentional_blink_data_set.zip] --> | ||
*[http://weblab1.psych.ubc.ca/wikiakje/uploads/akwikishr/gaze_cueing_data_set.zip gaze_cueing_data_set.zip] | <!-- *[http://weblab1.psych.ubc.ca/wikiakje/uploads/akwikishr/gaze_cueing_data_set.zip gaze_cueing_data_set.zip] --> | ||
*[http://real.psych.ubc.ca/images/1/14/Attentional_blink_data_set.zip attentional_blink_data_set.zip] | |||
*[http://real.psych.ubc.ca/images/0/03/Gaze_cueing_data_set.zip gaze_cueing_data_set.zip] | |||
(you can also find these in the bar.laboratory@gmail.com dropbox account, in the "\stats meetings\data sets" folder - please make copies for yourself as these should remain in this folder as originals) | (you can also find these in the bar.laboratory@gmail.com dropbox account, in the "\stats meetings\data sets" folder - please make copies for yourself as these should remain in this folder as originals) | ||
*[[R organizing data#how to make a new script?|how to make a new script?]] | *[[R organizing data#how to make a new script?|how to make a new script?]] | ||
Line 63: | Line 66: | ||
*[[R organizing data#changing your RT variable into a validity effect variable (invalid RT - valid RT)?|changing your RT variable into a validity effect variable (invalid RT - valid RT)?]] | *[[R organizing data#changing your RT variable into a validity effect variable (invalid RT - valid RT)?|changing your RT variable into a validity effect variable (invalid RT - valid RT)?]] | ||
====[[R organizing data#reorganizing your data for export to Excel/SPSS]]==== | ====[[R organizing data#reorganizing your data for export to Excel/SPSS|reorganizing your data for export to Excel/SPSS]]==== | ||
==[[R analyzing data|Part 3: Analyzing your data]]== | ==[[R analyzing data|Part 3: Analyzing your data]]== | ||
Line 88: | Line 91: | ||
*[[R analyzing data#Line graph template|Line graph template]] | *[[R analyzing data#Line graph template|Line graph template]] | ||
*[[R analyzing data#Customizing your graph|Customizing your graph]] | *[[R analyzing data#Customizing your graph|Customizing your graph]] | ||
Latest revision as of 19:49, 27 August 2015
This wiki is designed to help anyone perform statistical analyses on their data using R. It is divided into 3 broad sections: the first section outlines basics of how R deals with data using built in data sets, the second will help you to read in and organize your own data, and the third will help to summarize, run stats, and output graphs of your data.
Each section is organized into a series of questions. Start from the beginning if you are new to R, or click on a question to go to a detailed answer and/or examples.
To get started, download R for free from the R website
Alternatively, for a better organized scripting environment with syntax highlighting, download Rstudio
Part 1: R basics
- What is a data frame?
- Viewing the whole data frame?
- Viewing the head or tail of a data frame?
- Summary of data frame?
- Dimensions of your data frame?
- Viewing a single row or single column?
- Viewing multiple rows/columns?
- Single variable of the data frame?
- Commands on a single variable?
- Viewing and changing variable names?
- Creating a new variable from scratch?
- Creating a new variable based on values of another variable?
- Viewing cases of an IV that meet certain conditions?
- Finding the indices of an IV that meet certain conditions (which)?
- Finding values of one variable that correspond to values of another variable that meet certain conditions?
- Copying a data frame?
- General cautionary notes and help
- How to load a library/package to extend R functionality?
Part 2: Organizing your data
This section describes how to load in data files into a data frame, add or drop columns, create a new data frame from a subset of the full data, and generally get your data into the form you need so you can then conduct your analyses.
prep stuff: data sets & making a new script
First download the following data sets, and unzip them to a local folder:
(you can also find these in the bar.laboratory@gmail.com dropbox account, in the "\stats meetings\data sets" folder - please make copies for yourself as these should remain in this folder as originals)
how to read your data into R
- reading in a single delimited file?
- reading in multiple delimited files and storing into a main data frame?
- reading in files and creating a subject variable/other variable based on the file names?
- factorizing numerical IVs?
- summary of attentional_blink.R script so far?
- applying what we have learned so far to the gaze cueing data set?
how to fill out and complete your main data frame
- adding a new variable based on another variable (substr)?
- adding a new variable based on another variable (ifelse)?
- adding a new variable based on another variable (ifelse & substr)?
- adding a new variable based on another variable (selecting string subset by regular expression)
- adding a new variable based on another variable (logical statement using regular expressions)
how to select a subset of your main data frame
- selecting rows from your main data frame?
- example: RT cutoffs based on condition means?
- selecting columns and rows from your main data frame?
- changing your RT variable into a validity effect variable (invalid RT - valid RT)?
reorganizing your data for export to Excel/SPSS
Part 3: Analyzing your data
This section outlines how to perform descriptive stats, inferential stats, and output graphs once your data frame is organized
Performing ANOVAs
Means tables and simple plots
Follow-up tests
Following up on significant main effect of a factor with more than 2 levels
Following up on significant interaction
- Simple main effect of factor B at level of factor A
- Tukey's HSD tests for factor B at level of factor A