fish flanker

[tjmahr]

• determine what the fields in the trial-level mean, which ones to keep, how to document/rename them
• write a script to create a dataframe from a single FishFlanker file. apply to all existing files
• create database table for administrations and table for responses
• create queries that aggregate the response data
• incorporate into existing queries

[tjmahr]

notes

It looks like the trial-level data are in the PracItemsProc and TestItemsProc frames. I need to know what the variables in those parts mean.

Level Counts: 
 Eprime.Level          Running        Procedure freq
            1           Header           Header    1
            3 InstructionsList InstructionsProc    9
            3         ItemList    PracItemsProc    4
            2         TaskList     PracticeProc    1
            3         ItemList    TestItemsProc   40
            2         TaskList         TestProc    1
            1             <NA>             <NA>    1

 Eprime.Level  Running     Procedure
            3 ItemList TestItemsProc
List of 27
 $ Eprime.Level       : num 3
 $ Eprime.LevelName   : chr "ItemList_25"
 $ Eprime.Basename    : chr "FishFlanker_001L53FS5"
 $ Eprime.FrameNumber : chr "16"
 $ Procedure          : chr "TestItemsProc"
 $ Running            : chr "ItemList"
 $ StimType           : chr "Fish"
 $ FixationDur        : chr "1464"
 $ TaskPart           : chr "Fish"
 $ PartItem           : chr "1"
 $ Congruency         : chr "con"
 $ TargetDir          : chr "left"
 $ CorrectAnswer      : chr "LEFTARROW"
 $ Number             : chr ""
 $ Cycle              : chr "3"
 $ Sample             : chr "5"
 $ SoundVolume        : chr "0"
 $ ISI.OnsetDelay     : chr "29"
 $ Fixation.OnsetDelay: chr "0"
 $ Cue.OnsetDelay     : chr "2"
 $ Flankers.OnsetDelay: chr "0"
 $ Target.OnsetDelay  : chr "0"
 $ Target.RTTime      : chr "237884"
 $ Target.ACC         : chr "1"
 $ Target.RT          : chr "1790"
 $ Target.RESP        : chr "LEFTARROW"
 $ Target.CRESP       : chr ""

It looks like the important stuff are these fields

> df %>% select(Eprime.Basename, StimType:CorrectAnswer, Target.ACC:Target.CRESP)  %>% filter(!is.na(StimType))
Source: local data frame [6,068 x 12]

         Eprime.Basename StimType FixationDur TaskPart PartItem Congruency TargetDir CorrectAnswer Target.ACC Target.RT Target.RESP Target.CRESP
                   <chr>    <chr>       <chr>    <chr>    <chr>      <chr>     <chr>         <chr>      <chr>     <chr>       <chr>        <chr>
1  FishFlanker_001L53FS5     Fish        1460 Practice        1        con     right    RIGHTARROW          1      3815  RIGHTARROW             
2  FishFlanker_001L53FS5     Fish        1219 Practice        2        con      left     LEFTARROW          1       981   LEFTARROW             
3  FishFlanker_001L53FS5     Fish        1501 Practice        3        inc     right    RIGHTARROW          1      2673  RIGHTARROW             
4  FishFlanker_001L53FS5     Fish        1032 Practice        4        inc      left     LEFTARROW          0      4619  RIGHTARROW             
5  FishFlanker_001L53FS5     Fish        1464     Fish        1        con      left     LEFTARROW          1      1790   LEFTARROW             
6  FishFlanker_001L53FS5     Fish        1473     Fish        2        con     right    RIGHTARROW          1      2573  RIGHTARROW             
7  FishFlanker_001L53FS5     Fish        1155     Fish        3        inc     right    RIGHTARROW          1      4708  RIGHTARROW             
8  FishFlanker_001L53FS5     Fish        1068     Fish        4        con      left     LEFTARROW          0      1344  RIGHTARROW             
9  FishFlanker_001L53FS5     Fish        1476     Fish        5        inc     right    RIGHTARROW          1      6178  RIGHTARROW             
10 FishFlanker_001L53FS5     Fish        1313     Fish        6        con     right    RIGHTARROW          1      1610  RIGHTARROW             
11 FishFlanker_001L53FS5     Fish        1308     Fish        7        con      left     LEFTARROW          1      8231   LEFTARROW             
12 FishFlanker_001L53FS5     Fish        1067     Fish        8        inc      left     LEFTARROW          1      4151   LEFTARROW             
13 FishFlanker_001L53FS5     Fish        1352     Fish        9        con      left     LEFTARROW          0         0      NORESP             
14 FishFlanker_001L53FS5     Fish        1300     Fish       10        inc      left     LEFTARROW          1      5958   LEFTARROW             
15 FishFlanker_001L53FS5     Fish        1294     Fish       11        con     right    RIGHTARROW          1      1294  RIGHTARROW             
..                   ...      ...         ...      ...      ...        ...       ...           ...        ...       ...         ...          ...

With these columns, we have enough information to reconstruct the screen of the trial, assumng five fish in a flank 🐟

Source: local data frame [8 x 4]

  StimType Congruency TargetDir                                            Display
     <chr>      <chr>     <chr>                                              <chr>
1     Fish        con     right  ><(((('>  ><(((('>  ><(((('>  ><(((('>  ><(((('> 
2     Fish        con      left  <'))))><  <'))))><  <'))))><  <'))))><  <'))))>< 
3     Fish        inc     right  <'))))><  <'))))><  ><(((('>  <'))))><  <'))))>< 
4     Fish        inc      left  ><(((('>  ><(((('>  <'))))><  ><(((('>  ><(((('> 
5    Arrow        con      left                                <-  <-  <-  <-  <- 
6    Arrow        con     right                                ->  ->  ->  ->  -> 
7    Arrow        inc     right                                <-  <-  ->  <-  <- 
8    Arrow        inc      left                                ->  ->  <-  ->  -> 

Questions

• What does NORESP mean in the Target.RESP column?
• The Target.CRESP is sometimes not blank. When is it used?
• How is the Target.RT calculated? Is there an upper limit on it?

summary(as.numeric(df$Target.RT))
#>   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
#>      0    1429    1904    2456    2950   30060    2067