rprime is an R
package for parsing .txt generated by E-Prime, a program
for running psychological experiments.
The main workflow for rprime involves:
read_eprime: reliably read in data from an Eprime log
(.txt) file.FrameList: extract the text in each
"LogFrame" in the file, storing each log-frame as an R
list.preview_levels, preview_eprime: explore
the structure of the parsed data.keep_levels, drop_levels,
filter_in, filter_out: select and filter
particular levels from the txt-file.to_data_frame: make a data-frame from the parsed
data.Load the file with read_eprime and parse its contents
with FrameList.
In the text file, frames were distinguished by the procedure they are
running as well as the their level of nesting. Get an overview of the
different types of frames with preview_levels.
# There are six different kinds of frames in this file
preview_levels(experiment_data)
#> Level Counts:
#> Eprime.Level Running Procedure freq
#> 1 Header Header 1
#> 3 PracticeBlock PracticeTrialProc 10
#> 2 PracticeList PracticeProc 1
#> 3 TrialLists TrialProc 70
#> 2 BlockList BlockProc 7
#> 1 <NA> <NA> 1Get a preview of the data in each kind of frame with
preview_frames.
preview_frames(experiment_data)
#>
#> Eprime.Level Running Procedure
#> 1 Header Header
#> List of 22
#> $ Eprime.Level : num 1
#> $ Eprime.LevelName : chr "Header_"
#> $ Eprime.Basename : chr "SAILS_001X00XS1"
#> $ Eprime.FrameNumber : chr "1"
#> $ Procedure : chr "Header"
#> $ Running : chr "Header"
#> $ VersionPersist : chr "1"
#> $ LevelName : chr "LogLevel10"
#> $ Experiment : chr "SAILS"
#> $ SessionDate : chr "12-01-2013"
#> $ SessionTime : chr "11:00:00"
#> $ SessionTimeUtc : chr "5:00:00 PM"
#> $ Dilaect : chr "Yes"
#> $ Subject : chr "001"
#> $ ExpTyp : chr "X"
#> $ Age : chr "00"
#> $ Gender : chr "X"
#> $ Session : chr "1"
#> $ ChildNativeDialect : chr "S"
#> $ RandomSeed : chr "-676084859"
#> $ Group : chr "1"
#> $ Display.RefreshRate: chr "60.004"
#> - attr(*, "class")= chr [1:2] "EprimeFrame" "list"
#>
#> Eprime.Level Running Procedure
#> 3 PracticeBlock PracticeTrialProc
#> List of 25
#> $ Eprime.Level : num 3
#> $ Eprime.LevelName : chr "PracticeBlock_1"
#> $ Eprime.Basename : chr "SAILS_001X00XS1"
#> $ Eprime.FrameNumber : chr "2"
#> $ Procedure : chr "PracticeTrialProc"
#> $ Running : chr "PracticeBlock"
#> $ Practice : chr "1"
#> $ Sound : chr "LAKE1.WAV"
#> $ Correct : chr "Word"
#> $ Module : chr "LAKE"
#> $ Color : chr "red"
#> $ WordImage : chr "lake"
#> $ NonWordImage : chr "notlake"
#> $ PuzzleImage : chr "up"
#> $ Cycle : chr "1"
#> $ Sample : chr "1"
#> $ TrialSlide.OnsetDelay : chr "197"
#> $ TrialSlide.OnsetTime : chr "899413"
#> $ TrialSlide.DurationError: chr "-999999"
#> $ TrialSlide.RTTime : chr "0"
#> $ TrialSlide.ACC : chr "0"
#> $ TrialSlide.RT : chr "0"
#> $ TrialSlide.RESP : chr ""
#> $ TrialSlide.CRESP : chr ""
#> $ Response : chr "Word"
#> - attr(*, "class")= chr [1:2] "EprimeFrame" "list"
#>
#> Eprime.Level Running Procedure
#> 2 PracticeList PracticeProc
#> List of 11
#> $ Eprime.Level : num 2
#> $ Eprime.LevelName : chr "PracticeList_1"
#> $ Eprime.Basename : chr "SAILS_001X00XS1"
#> $ Eprime.FrameNumber: chr "12"
#> $ Procedure : chr "PracticeProc"
#> $ Running : chr "PracticeList"
#> $ Cycle : chr "1"
#> $ Sample : chr "1"
#> $ PuzzleMovie : chr "up"
#> $ TrainingNonWord : chr "notlake"
#> $ TrainingWord : chr "lake"
#> - attr(*, "class")= chr [1:2] "EprimeFrame" "list"
#>
#> Eprime.Level Running Procedure
#> 3 TrialLists TrialProc
#> List of 25
#> $ Eprime.Level : num 3
#> $ Eprime.LevelName : chr "TrialLists_1"
#> $ Eprime.Basename : chr "SAILS_001X00XS1"
#> $ Eprime.FrameNumber : chr "13"
#> $ Procedure : chr "TrialProc"
#> $ Running : chr "TrialLists"
#> $ Sound : chr "LAKE23B.WAV"
#> $ Correct : chr "Word"
#> $ LakeLevel1 : chr "8"
#> $ Module : chr "LAKE"
#> $ Color : chr "blue"
#> $ WordImage : chr "lake"
#> $ NonWordImage : chr "notlake"
#> $ PuzzleImage : chr "butterfly"
#> $ TrialSlide.OnsetDelay : chr "119"
#> $ TrialSlide.OnsetTime : chr "1023939"
#> $ TrialSlide.DurationError: chr "-999999"
#> $ TrialSlide.RTTime : chr "0"
#> $ TrialSlide.ACC : chr "0"
#> $ TrialSlide.RT : chr "0"
#> $ TrialSlide.RESP : chr ""
#> $ TrialSlide.CRESP : chr ""
#> $ Response : chr "Word"
#> $ Cycle : chr "1"
#> $ Sample : chr "1"
#> - attr(*, "class")= chr [1:2] "EprimeFrame" "list"
#>
#> Eprime.Level Running Procedure
#> 2 BlockList BlockProc
#> List of 11
#> $ Eprime.Level : num 2
#> $ Eprime.LevelName : chr "BlockList_1"
#> $ Eprime.Basename : chr "SAILS_001X00XS1"
#> $ Eprime.FrameNumber: chr "23"
#> $ Procedure : chr "BlockProc"
#> $ Running : chr "BlockList"
#> $ PuzzleMovie : chr "butterfly"
#> $ TrainingNonWord : chr "notlake"
#> $ TrainingWord : chr "lake"
#> $ Cycle : chr "1"
#> $ Sample : chr "1"
#> - attr(*, "class")= chr [1:2] "EprimeFrame" "list"
#>
#> Eprime.Level Running Procedure
#> 1 <NA> <NA>
#> List of 20
#> $ Eprime.Level : num 1
#> $ Eprime.LevelName : logi NA
#> $ Eprime.Basename : chr "SAILS_001X00XS1"
#> $ Eprime.FrameNumber : chr "90"
#> $ Procedure : logi NA
#> $ Running : logi NA
#> $ Experiment : chr "SAILS"
#> $ SessionDate : chr "12-01-2013"
#> $ SessionTime : chr "11:00:00"
#> $ SessionTimeUtc : chr "5:00:00 PM"
#> $ Dilaect : chr "Yes"
#> $ Subject : chr "001"
#> $ ExpTyp : chr "X"
#> $ Age : chr "00"
#> $ Gender : chr "X"
#> $ Session : chr "1"
#> $ ChildNativeDialect : chr "S"
#> $ RandomSeed : chr "-676084859"
#> $ Group : chr "1"
#> $ Display.RefreshRate: chr "60.004"
#> - attr(*, "class")= chr [1:2] "EprimeFrame" "list"preview_eprime (not demonstrated here) does both kinds
of previews (levels and frames).
Use keep_levels and drop_levels to filter
frames according to nesting level.
# Filter (out) by depth of nesting
not_level_1 <- drop_levels(experiment_data, 1)
preview_levels(not_level_1)
#> Level Counts:
#> Eprime.Level Running Procedure freq
#> 3 PracticeBlock PracticeTrialProc 10
#> 2 PracticeList PracticeProc 1
#> 3 TrialLists TrialProc 70
#> 2 BlockList BlockProc 7
# Filter (in) by depth of nesting
just_level_3 <- keep_levels(experiment_data, 3)
preview_levels(just_level_3)
#> Level Counts:
#> Eprime.Level Running Procedure freq
#> 3 PracticeBlock PracticeTrialProc 10
#> 3 TrialLists TrialProc 70Use filter_in and filter_out to filter
frames using attribute values. Use repeated filtering statements to
drill down into the list of frames.
# Filter (out) by attribute values
no_header <- filter_out(experiment_data, "Running", values = "Header")
preview_levels(no_header)
#> Level Counts:
#> Eprime.Level Running Procedure freq
#> 3 PracticeBlock PracticeTrialProc 10
#> 2 PracticeList PracticeProc 1
#> 3 TrialLists TrialProc 70
#> 2 BlockList BlockProc 7
#> 1 <NA> <NA> 1
# Filter (in) by attribute values
not_practice <- filter_in(experiment_data, "Running", "TrialLists")
preview_levels(not_practice)
#> Level Counts:
#> Eprime.Level Running Procedure freq
#> 3 TrialLists TrialProc 70
# Drill down further into the trials by filtering again
sue_trials <- filter_in(not_practice, "Module", "SUE")
preview_eprime(sue_trials)
#> Level Counts:
#> Eprime.Level Running Procedure freq
#> 3 TrialLists TrialProc 30
#>
#> Eprime.Level Running Procedure
#> 3 TrialLists TrialProc
#> List of 25
#> $ Eprime.Level : num 3
#> $ Eprime.LevelName : chr "TrialLists_5"
#> $ Eprime.Basename : chr "SAILS_001X00XS1"
#> $ Eprime.FrameNumber : chr "57"
#> $ Procedure : chr "TrialProc"
#> $ Running : chr "TrialLists"
#> $ Sound : chr "SUE4.WAV"
#> $ Correct : chr "Word"
#> $ SueLevel1 : chr "10"
#> $ Module : chr "SUE"
#> $ Color : chr "blue"
#> $ WordImage : chr "sue"
#> $ NonWordImage : chr "notsue"
#> $ PuzzleImage : chr "madagascar"
#> $ TrialSlide.OnsetDelay : chr "127"
#> $ TrialSlide.OnsetTime : chr "1360767"
#> $ TrialSlide.DurationError: chr "-999999"
#> $ TrialSlide.RTTime : chr "0"
#> $ TrialSlide.ACC : chr "0"
#> $ TrialSlide.RT : chr "0"
#> $ TrialSlide.RESP : chr ""
#> $ TrialSlide.CRESP : chr ""
#> $ Response : chr "Word"
#> $ Cycle : chr "1"
#> $ Sample : chr "41"
#> - attr(*, "class")= chr [1:2] "EprimeFrame" "list"Convert to a dataframe with to_dataframe. Attribute
names in the log-frames become column names in the dataframe.
# Export to dataframe
sue_trials_df <- to_data_frame(sue_trials)
str(sue_trials_df)
#> 'data.frame': 30 obs. of 27 variables:
#> $ Eprime.Level : num 3 3 3 3 3 ...
#> $ Eprime.LevelName : chr "TrialLists_5" "TrialLists_5" ...
#> $ Eprime.Basename : chr "SAILS_001X00XS1" "SAILS_001X00XS1" ...
#> $ Eprime.FrameNumber : chr "57" "58" ...
#> $ Procedure : chr "TrialProc" "TrialProc" ...
#> $ Running : chr "TrialLists" "TrialLists" ...
#> $ Sound : chr "SUE4.WAV" "SUE15.WAV" ...
#> $ Correct : chr "Word" "NotWord" ...
#> $ SueLevel1 : chr "10" "2" ...
#> $ Module : chr "SUE" "SUE" ...
#> $ Color : chr "blue" "blue" ...
#> $ WordImage : chr "sue" "sue" ...
#> $ NonWordImage : chr "notsue" "notsue" ...
#> $ PuzzleImage : chr "madagascar" "madagascar" ...
#> $ TrialSlide.OnsetDelay : chr "127" "98" ...
#> $ TrialSlide.OnsetTime : chr "1360767" "1364450" ...
#> $ TrialSlide.DurationError: chr "-999999" "-999999" ...
#> $ TrialSlide.RTTime : chr "0" "0" ...
#> $ TrialSlide.ACC : chr "0" "0" ...
#> $ TrialSlide.RT : chr "0" "0" ...
#> $ TrialSlide.RESP : chr "" "" ...
#> $ TrialSlide.CRESP : chr "" "" ...
#> $ Response : chr "Word" "NotWord" ...
#> $ Cycle : chr "1" "1" ...
#> $ Sample : chr "41" "42" ...
#> $ SueLevel2 : chr NA NA ...
#> $ SueLevel3 : chr NA NA ...
# Don't need every column
columns_to_keep <- c("Eprime.Basename", "Module", "Sample",
"Correct", "Response")
sue_trials_df <- sue_trials_df[columns_to_keep]
head(sue_trials_df)
#> Eprime.Basename Module Sample Correct Response
#> 1 SAILS_001X00XS1 SUE 41 Word Word
#> 2 SAILS_001X00XS1 SUE 42 NotWord NotWord
#> 3 SAILS_001X00XS1 SUE 43 NotWord Word
#> 4 SAILS_001X00XS1 SUE 44 Word Word
#> 5 SAILS_001X00XS1 SUE 45 NotWord NotWord
#> 6 SAILS_001X00XS1 SUE 46 Word WordNote: rprime thinks that all the values in the final
dataframe are character values. You can use type_convert in
the readr package to correct the column types:
# Right now the sample numbers are stored as character values
str(sue_trials_df)
#> 'data.frame': 30 obs. of 5 variables:
#> $ Eprime.Basename: chr "SAILS_001X00XS1" "SAILS_001X00XS1" ...
#> $ Module : chr "SUE" "SUE" ...
#> $ Sample : chr "41" "42" ...
#> $ Correct : chr "Word" "NotWord" ...
#> $ Response : chr "Word" "NotWord" ...
library("readr")
sue_trials_df <- type_convert(sue_trials_df)
#>
#> ── Column specification ────────────────────────────────────────────────────────
#> cols(
#> Eprime.Basename = col_character(),
#> Module = col_character(),
#> Sample = col_double(),
#> Correct = col_character(),
#> Response = col_character()
#> )
# Now, they are stored as integers...
str(sue_trials_df)
#> 'data.frame': 30 obs. of 5 variables:
#> $ Eprime.Basename: chr "SAILS_001X00XS1" "SAILS_001X00XS1" ...
#> $ Module : chr "SUE" "SUE" ...
#> $ Sample : num 41 42 43 44 45 ...
#> $ Correct : chr "Word" "NotWord" ...
#> $ Response : chr "Word" "NotWord" ...