crp.RdThis function calculates the conditional response probability of each lag position. Participants' lag between subsequent named items is tallied and then divided by the possible combination of subsequent lags given their response pattern.
crp(data, position, answer, id, key, scored)a dataframe of the scored free recall that you would like to calculate - use prop_correct_free() for best formatting.
a column name in the dataframe that contains answered position of each response in quotes (i.e., "column")
a column name of the answer given for that position in the original dataframe.
a column name of the participant id in the original dataframe.
a vector containing the scoring key or data column name. This column does not have to be included in the original dataframe. We assume your answer key is in the tested position order. You should not include duplicates in your answer key.
a column in the original dataframe indicating if the participant got the answer correct (1) or incorrect (0).
A dataframe of the proportion correct for each conditional lag position including any other between subjects variables present in the data.
This output can then be used to create a CRP visualizations, and an example can be found in our manuscript/vignettes.
Important: The code is written assuming the data provided are for a single recall list. If repeated measures are used (i.e., there are multiple lists completed by each participant or multiple list versions), you should use this function several times, once on each list/answer key.
data(free_data)
data(answer_key_free2)
free_data <- subset(free_data,
List_Type == "Cat_Recall_L1")
DF_long <- arrange_data(data = free_data,
responses = "Response",
sep = " ",
id = "Username")
scored_output <- prop_correct_free( data = DF_long,
responses = "response",
key = answer_key_free2$Answer_Key,
id = "Sub.ID",
cutoff = 1,
flag = TRUE,
group.by = "Version")
crp_output <- crp(data = scored_output$DF_Scored,
position = "position",
answer = "Answer",
id = "Sub.ID",
key = answer_key_free2$Answer_Key,
scored = "Scored")
head(crp_output)
#> Sub.ID participant_lags Freq Possible.Freq List_Type Version
#> 1 B22HXP5RIG37XD -19 0 0 Cat_Recall_L1 E
#> 2 B22HXP5RIG37XD -18 0 0 Cat_Recall_L1 E
#> 3 B22HXP5RIG37XD -17 0 0 Cat_Recall_L1 E
#> 4 B22HXP5RIG37XD -16 0 0 Cat_Recall_L1 E
#> 5 B22HXP5RIG37XD -15 1 4 Cat_Recall_L1 E
#> 6 B22HXP5RIG37XD -14 0 0 Cat_Recall_L1 E
#> Batch CRP
#> 1 1 0.00
#> 2 1 0.00
#> 3 1 0.00
#> 4 1 0.00
#> 5 1 0.25
#> 6 1 0.00