Analyzing your data for the Strack RRR
The primary data analysis for the Strack RRR will be conducted by the lead lab. That
analysis will take your raw data files and will conduct all of the individual analyses and
the meta-analysis that will go into the final report.
Each individual lab can also conduct the analyses on their own data. To make that
easier, the lead lab has written an R script that will perform all of the necessary
analyses and will provide you with output files containing your coded and analyzed data.
Below we provide a step-by-step guide on using this script. If you have any questions
about the scripts or problems getting it to work, please email [email protected].
First, you need to install both R and R studio (both are free and open-source).
Step 1: Go to http://cran.r-project.org/ and download R for your computer platform.
Step 2: Go to http://www.rstudio.com/products/rstudio/download/ and download RStudio
for your platform.
Step 3: Create a folder where you will place the necessary scripts and your data file.
You can name the folder whatever you want, but we’d recommend naming it
“RRR_Strack” and will call it that throughout these instructions.
Step 4: Put the files (from our email) called analysis.R and Repfunctionspack.R into the
RRR_Strack folder.
Step 5: Open the RRR_Strack folder and create a folder inside of it named “Data” —
the capitalization matters, so make sure it has a capital D.
Step 6: Put your own Excel-formatted datafile into the new Data folder you created.
Your data file should have been created using the template we provided (called
TemplateDatafile.xlsx). The scripts will only work if they have that format. Name your
data file with your last name like this: “Simons_Data.xlsx” — the file must end
with .xlsx.
Step 7: Open the RStudio application. It might take a while the first time you open it.
Step 8: Click the File menu in the upper left corner of the RStudio window and choose
Open File
Step 9: Choose the file named analysis.R that is in your RRR_Strack folder.
Step 10: Set the working directory to your RRR_Strack folder. To do that, click on the
Session menu option in RStudio, choose Set Working Directory, and then choose To
Source File Location (see figure below)
Step 11: You can now run the analysis. To do that, click the Source button at the far
right of the window showing the analysis.R file (see Figure below).
Step 12: Wait for the analysis to finish — it may take some time. It will be complete
when the red “stop” sign disappears.
Step 13: Look in your RRR_Strack folder. You’ll see two new files:
resultsFacialFeedbackReplication.xlsx and resultsFacialFeedbackReplication.csv.
Those files are just differently formatted versions of the same output, one is an Excel file
and one has comma-separated text. They include the output of all of the analyses.
Below is a key to the contents of those files.
Key to the output file contents
studyIDs: study identifier, which will be 1_nameOfYourXlsxFile if you analyze only one study.
meanSmileEx: mean in the smile condition after excluding participants according to the
exclusion criteria.
meanPoutEx: mean in the pout condition after excluding participants according to the exclusion
criteria.
sdSmileEx: standard deviation in the smile condition after excluding participants according to
the exclusion criteria.
sdPoutEx: standard deviation in the pout condition after excluding participants according to the
exclusion criteria.
nSmileEx: number of participants in the smile condition after excluding participants according to
the exclusion criteria.
nSmileExcluded: number of participants in the smile condition that have been excluded
according to the exclusion criteria.
nPoutEx: number of participants in the pout condition after excluding participants according to
the exclusion criteria.
nPoutExcluded: number of participants in the pout condition that have been excluded
according to the exclusion criteria.
tValueEx: t-value of a classical one-sided independent samples t-test assuming equal variances
testing the hypothesis that the mean in the smile condition is larger (after participants have
been excluded according to exclusion criteria).
dfEx: df of that t-test.
pValueEx: p-value of that t-test.
BFplus0Ex: independent samples t-test Bayes factor in favor of the hypothesis that the smile
condition has a larger mean rating, ( cauchy prior width = 1/sqrt(2) ), after participants
have been excluded according to the exclusion criteria.
BFr0Ex: replication Bayes factor as proposed in Verhagen & Wagenmakers (2014), after
participants have been excluded according to the exclusion criteria.
gEx: Hedges' g effect size after participants have been excluded according to the exclusion
criteria.
gSEEx: standard error of Hedges' g after participants have been excluded according to the
exclusion criteria.
gLowerCIEx: lower bound of 95% confidence interval for Hedges' g after participants have
been excluded according to the exclusion criteria.
gUpperCIEx: upper bound of 95% confidence interval for Hedges' g after participants have
been excluded according to the exclusion criteria.
dEx: Cohen's d effect size after participants have been excluded according to the exclusion
criteria.
dSEEx: standard error of Cohen's d after participants have been excluded according to the
exclusion criteria.
dLowerCIEx: lower bound of 95% confidence interval for Cohen's d after participants have
been excluded according to the exclusion criteria.
dUpperCIEx: upper bound of 95% confidence interval for Cohen's d after participants have
been excluded according to the exclusion criteria.
rawMeanDiffEx: difference between mean in smile condition and pout condition after
participants have been excluded according to the exclusion criteria.
meanSmileAll: mean in the smile condition when considering all participants (without
exclusion).
meanPoutAll: mean in the pout condition when considering all participants (without exclusion).
sdSmileAll: standard deviation in the smile condition when considering all participants (without
exclusion).
sdPoutAll: standard deviation in the pout condition when considering all participants (without
exclusion).
nSmileAll: number of participants in the smile condition when considering all participants
(without exclusion).
nPoutAll: number of participants in the pout condition when considering all participants (without
exclusion).
tValueAll: t-value of a classical one-sided independent samples t-test assuming equal
variances testing the hypothesis that the mean in the smile condition is larger, when
considering all participants (without exclusion).
dfAll: df of that t-test.
pValueAll: p-value of that t-test.
BFplus0All: independent samples t-test Bayes factor in favor of the hypothesis that the smile
condition has a larger mean rating, ( cauchy prior width = 1/sqrt(2) ), when considering all
participants (without exclusion).
BFr0All: replication Bayes factor as proposed in Verhagen & Wagenmakers (2014), when
considering all participants (without exclusion).
gAll: Hedges' g effect size when considering all participants (without exclusion).
gSEAll: standard error of Hedges' g when considering all participants (without exclusion).
gLowerCIAll: lower bound of 95% confidence interval for Hedges' g when considering all
participants (without exclusion).
gUpperCIAll: upper bound of 95% confidence interval for Hedges' g when considering all
participants (without exclusion).
dAll: Cohen's d effect size when considering all participants (without exclusion).
dSEAll: standard error of Cohen's d when considering all participants (without exclusion).
dLowerCIAll: lower bound of 95% confidence interval for Cohen's d when considering all
participants (without exclusion).
dUpperCIAll: upper bound of 95% confidence interval for Cohen's d when considering all
participants (without exclusion).
rawMeanDiffAll: difference between mean in smile condition and pout condition when
considering all participants (without exclusion).