Libraries and Data

Please see manuscript for a long description of the following data. We will load the example data, and you can use the ? with the dataset name to learn more about the data.

library(lrd)
#> 
#> Attaching package: 'lrd'
#> The following object is masked from 'package:base':
#> 
#>     kappa
data("cued_recall_manuscript")
head(cued_recall_manuscript)
#>   Sub.ID Trial_num          Cue      Target      Answer
#> 1      1         1 chlorination ideological ideological
#> 2      1         2        bendy   financial   financial
#> 3      1         3   topography     editing     editing
#> 4      1         4      enquiry     buzzing     buzzing
#> 5      1         5    draconian   statistic   statistic
#> 6      1         6    speedball   stopwatch   stopwatch
#?cued_recall_manuscript

Data Cleanup

Scoring in lrd is case sensitive, so we will use tolower() to lower case all correct answers and participant answers.

cued_recall_manuscript$Target <- tolower(cued_recall_manuscript$Target)
cued_recall_manuscript$Answer <- tolower(cued_recall_manuscript$Answer)

Score the Data

You should define the following:

  • data = dataframe of participant responses
  • responses = column name of the participant answers
  • key = column name of the answer key
  • key.trial = column name of the trial id code
  • id = column name of the participant id number
  • id.trial = column name of the trial id within the participant data
  • cutoff = the Levenshtein distance value you want to use for scoring (0 no changes exactly the same, higher numbers allow more variance in the word)
  • flag = calculate z scores for outliers (TRUE/FALSE)
  • group.by = column name(s) for grouping variables

Note that the answer key can be in a separate dataframe, use something like answer_key$answer for the key argument and answer_key$id_num for the trial number. Fill in answer_key with your dataframe name and the column name for those columns after the $.

cued_output <- prop_correct_cued(data = cued_recall_manuscript,
                                 responses = "Answer",
                                 key = "Target",
                                 key.trial = "Trial_num",
                                 id = "Sub.ID",
                                 id.trial = "Trial_num",
                                 cutoff = 1,
                                 flag = TRUE,
                                 group.by = NULL)

str(cued_output)
#> List of 2
#>  $ DF_Scored     :'data.frame':  120 obs. of  7 variables:
#>   ..$ Trial.ID : int [1:120] 1 1 1 1 1 1 2 2 2 2 ...
#>   ..$ Sub.ID   : int [1:120] 1 3 5 2 4 6 6 5 2 1 ...
#>   ..$ Cue      : chr [1:120] "chlorination" "chlorination" "chlorination" "chlorination" ...
#>   ..$ Target   : chr [1:120] "ideological" "ideological" "ideological" "ideological" ...
#>   ..$ Responses: chr [1:120] "ideological" "ideological" "ideological" "idological" ...
#>   ..$ Answer   : chr [1:120] "ideological" "ideological" "ideological" "ideological" ...
#>   ..$ Scored   : num [1:120] 1 1 1 1 1 0 0 0 1 1 ...
#>  $ DF_Participant:'data.frame':  6 obs. of  3 variables:
#>   ..$ Sub.ID             : int [1:6] 1 2 3 4 5 6
#>   ..$ Proportion.Correct : num [1:6] 1 0.8 0.85 0.95 0.75 0.45
#>   ..$ Z.Score.Participant: num [1:6, 1] 1.026 0 0.256 0.769 -0.256 ...
#>   .. ..- attr(*, "scaled:center")= num 0.8
#>   .. ..- attr(*, "scaled:scale")= num 0.195

Output

We can use DF_Scored to see the original dataframe with our new scored column - also to check if our answer key and participant answers matched up correctly! The DF_Participant can be used to view a participant level summary of the data. Last, if a grouping variable is used, we can use DF_Group to see that output.

#Overall
cued_output$DF_Scored
#>     Trial.ID Sub.ID              Cue       Target    Responses       Answer
#> 1          1      1     chlorination  ideological  ideological  ideological
#> 2          1      3     chlorination  ideological  ideological  ideological
#> 3          1      5     chlorination  ideological  ideological  ideological
#> 4          1      2     chlorination  ideological   idological  ideological
#> 5          1      4     chlorination  ideological  ideologicel  ideological
#> 6          1      6     chlorination  ideological               ideological
#> 7          2      6            bendy    financial        money    financial
#> 8          2      5            bendy    financial        money    financial
#> 9          2      2            bendy    financial    financial    financial
#> 10         2      1            bendy    financial    financial    financial
#> 11         2      3            bendy    financial    financial    financial
#> 12         2      4            bendy    financial    finenciel    financial
#> 13         3      5       topography      editing      editing      editing
#> 14         3      3       topography      editing     editting      editing
#> 15         3      6       topography      editing      editing      editing
#> 16         3      1       topography      editing      editing      editing
#> 17         3      4       topography      editing      editing      editing
#> 18         3      2       topography      editing       diting      editing
#> 19         4      5          enquiry      buzzing      buzzing      buzzing
#> 20         4      3          enquiry      buzzing      buzzing      buzzing
#> 21         4      6          enquiry      buzzing      buzzing      buzzing
#> 22         4      1          enquiry      buzzing      buzzing      buzzing
#> 23         4      4          enquiry      buzzing      buzzing      buzzing
#> 24         4      2          enquiry      buzzing      buzzing      buzzing
#> 25         5      5        draconian    statistic    statistic    statistic
#> 26         5      3        draconian    statistic sttattisttic    statistic
#> 27         5      6        draconian    statistic         math    statistic
#> 28         5      1        draconian    statistic    statistic    statistic
#> 29         5      4        draconian    statistic    stetistic    statistic
#> 30         5      2        draconian    statistic    statistic    statistic
#> 31         6      3        speedball    stopwatch  sttopwattch    stopwatch
#> 32         6      4        speedball    stopwatch    stopwetch    stopwatch
#> 33         6      6        speedball    stopwatch        watch    stopwatch
#> 34         6      5        speedball    stopwatch    stopwatch    stopwatch
#> 35         6      2        speedball    stopwatch    stopwatch    stopwatch
#> 36         6      1        speedball    stopwatch    stopwatch    stopwatch
#> 37         7      1        valueless          did          did          did
#> 38         7      3        valueless          did          did          did
#> 39         7      5        valueless          did         done          did
#> 40         7      2        valueless          did          did          did
#> 41         7      4        valueless          did          did          did
#> 42         7      6        valueless          did         done          did
#> 43         8      6         grievous  numerically  numerically  numerically
#> 44         8      3         grievous  numerically  numerically  numerically
#> 45         8      5         grievous  numerically  numerically  numerically
#> 46         8      2         grievous  numerically   numrically  numerically
#> 47         8      1         grievous  numerically  numerically  numerically
#> 48         8      4         grievous  numerically  numericelly  numerically
#> 49         9      6        melatonin      bloated      bloated      bloated
#> 50         9      1        melatonin      bloated      bloated      bloated
#> 51         9      5        melatonin      bloated      bloated      bloated
#> 52         9      4        melatonin      bloated      bloeted      bloated
#> 53         9      3        melatonin      bloated     bloatted      bloated
#> 54         9      2        melatonin      bloated       bloatd      bloated
#> 55        10      6             dose       domain         area       domain
#> 56        10      5             dose       domain         area       domain
#> 57        10      4             dose       domain       domein       domain
#> 58        10      3             dose       domain       domain       domain
#> 59        10      2             dose       domain       domain       domain
#> 60        10      1             dose       domain       domain       domain
#> 61        11      6     dynastically     steadily                  steadily
#> 62        11      5     dynastically     steadily     steadily     steadily
#> 63        11      4     dynastically     steadily     steedily     steadily
#> 64        11      3     dynastically     steadily    stteadily     steadily
#> 65        11      2     dynastically     steadily      stadily     steadily
#> 66        11      1     dynastically     steadily     steadily     steadily
#> 67        12      5          staffer     withdraw     withdraw     withdraw
#> 68        12      4          staffer     withdraw     withdrew     withdraw
#> 69        12      3          staffer     withdraw    witthdraw     withdraw
#> 70        12      2          staffer     withdraw     withdraw     withdraw
#> 71        12      6          staffer     withdraw     withdraw     withdraw
#> 72        12      1          staffer     withdraw     withdraw     withdraw
#> 73        13      3 institutionalism       beside       beside       beside
#> 74        13      6 institutionalism       beside       beside       beside
#> 75        13      5 institutionalism       beside       beside       beside
#> 76        13      2 institutionalism       beside         bsid       beside
#> 77        13      4 institutionalism       beside       beside       beside
#> 78        13      1 institutionalism       beside       beside       beside
#> 79        14      1        dollhouse       doodle       doodle       doodle
#> 80        14      3        dollhouse       doodle       doodle       doodle
#> 81        14      5        dollhouse       doodle         draw       doodle
#> 82        14      2        dollhouse       doodle        doodl       doodle
#> 83        14      4        dollhouse       doodle       doodle       doodle
#> 84        14      6        dollhouse       doodle         draw       doodle
#> 85        15      6           bolero     membrane     membrane     membrane
#> 86        15      5           bolero     membrane     membrane     membrane
#> 87        15      2           bolero     membrane       mmbran     membrane
#> 88        15      1           bolero     membrane     membrane     membrane
#> 89        15      3           bolero     membrane     membrane     membrane
#> 90        15      4           bolero     membrane     membrene     membrane
#> 91        16      5         soulless unofficially unofficially unofficially
#> 92        16      3         soulless unofficially unofficially unofficially
#> 93        16      6         soulless unofficially              unofficially
#> 94        16      1         soulless unofficially unofficially unofficially
#> 95        16      4         soulless unofficially unofficielly unofficially
#> 96        16      2         soulless unofficially unofficially unofficially
#> 97        17      5         uncurled    vibration    vibration    vibration
#> 98        17      3         uncurled    vibration   vibrattion    vibration
#> 99        17      6         uncurled    vibration    vibration    vibration
#> 100       17      1         uncurled    vibration    vibration    vibration
#> 101       17      4         uncurled    vibration    vibretion    vibration
#> 102       17      2         uncurled    vibration    vibration    vibration
#> 103       18      5         giveaway    permitted    permitted    permitted
#> 104       18      3         giveaway    permitted  permitttted    permitted
#> 105       18      6         giveaway    permitted      granted    permitted
#> 106       18      1         giveaway    permitted    permitted    permitted
#> 107       18      4         giveaway    permitted    permitted    permitted
#> 108       18      2         giveaway    permitted      prmittd    permitted
#> 109       19      3      origination        sleek        sleek        sleek
#> 110       19      4      origination        sleek        sleek        sleek
#> 111       19      6      origination        sleek        shiny        sleek
#> 112       19      5      origination        sleek        shiny        sleek
#> 113       19      2      origination        sleek          slk        sleek
#> 114       19      1      origination        sleek        sleek        sleek
#> 115       20      1        iconology    ignorance    ignorance    ignorance
#> 116       20      3        iconology    ignorance    ignorance    ignorance
#> 117       20      5        iconology    ignorance    ignorance    ignorance
#> 118       20      2        iconology    ignorance     ignoranc    ignorance
#> 119       20      4        iconology    ignorance    ignorence    ignorance
#> 120       20      6        iconology    ignorance    ignorance    ignorance
#>     Scored
#> 1        1
#> 2        1
#> 3        1
#> 4        1
#> 5        1
#> 6        0
#> 7        0
#> 8        0
#> 9        1
#> 10       1
#> 11       1
#> 12       0
#> 13       1
#> 14       1
#> 15       1
#> 16       1
#> 17       1
#> 18       1
#> 19       1
#> 20       1
#> 21       1
#> 22       1
#> 23       1
#> 24       1
#> 25       1
#> 26       0
#> 27       0
#> 28       1
#> 29       1
#> 30       1
#> 31       0
#> 32       1
#> 33       0
#> 34       1
#> 35       1
#> 36       1
#> 37       1
#> 38       1
#> 39       0
#> 40       1
#> 41       1
#> 42       0
#> 43       1
#> 44       1
#> 45       1
#> 46       1
#> 47       1
#> 48       1
#> 49       1
#> 50       1
#> 51       1
#> 52       1
#> 53       1
#> 54       1
#> 55       0
#> 56       0
#> 57       1
#> 58       1
#> 59       1
#> 60       1
#> 61       0
#> 62       1
#> 63       1
#> 64       1
#> 65       1
#> 66       1
#> 67       1
#> 68       1
#> 69       1
#> 70       1
#> 71       1
#> 72       1
#> 73       1
#> 74       1
#> 75       1
#> 76       0
#> 77       1
#> 78       1
#> 79       1
#> 80       1
#> 81       0
#> 82       1
#> 83       1
#> 84       0
#> 85       1
#> 86       1
#> 87       0
#> 88       1
#> 89       1
#> 90       1
#> 91       1
#> 92       1
#> 93       0
#> 94       1
#> 95       1
#> 96       1
#> 97       1
#> 98       1
#> 99       1
#> 100      1
#> 101      1
#> 102      1
#> 103      1
#> 104      0
#> 105      0
#> 106      1
#> 107      1
#> 108      0
#> 109      1
#> 110      1
#> 111      0
#> 112      0
#> 113      0
#> 114      1
#> 115      1
#> 116      1
#> 117      1
#> 118      1
#> 119      1
#> 120      1

#Participant
cued_output$DF_Participant
#>   Sub.ID Proportion.Correct Z.Score.Participant
#> 1      1               1.00           1.0259784
#> 2      2               0.80           0.0000000
#> 3      3               0.85           0.2564946
#> 4      4               0.95           0.7694838
#> 5      5               0.75          -0.2564946
#> 6      6               0.45          -1.7954621