[Chloris]

Thanks for providing the latest tutorial! I referred to this tutorial https://www.linguisticsociety.org/sites/default/files/PCIbex_Tutorial%5B2%5D.pdf when writing R codes…

Could you suggest a more unequivocal way of calculating the RTs?

Many thanks,
Chloris

[Chloris]

The same problem also occurred in my other experiment:
https://farm.pcibex.net/r/Iwjgkg/

It happened to fr24, still not very frequent – only once, but perplexing.

[Chloris]

Hi Jeremy,

Thanks a lot for your reply! My experiment asked participants to rate French words according to certain criteria. I got the table by selecting relevant columns and then selecting certain words (rows) in R:

# select and rename relevant columns
tidied_val <- results_val %>%
  filter(Parameter == "Choice" | Value == "Start") %>%
  select(ID, group, entry, Label, Parameter, PennElementName, Value, EventTime, word_id) %>%
  group_by(group, ID, entry) %>%
  mutate(RT = (mean(EventTime[Parameter=="Choice"] - EventTime[Value=="Start"]))/10)  %>%
  ungroup() %>%
  filter(Parameter == "Choice")  %>%
  select(ID, group, Value, entry, RT, Label, word_id) %>%
  rename(score = Value)

# quality check (valence)
quality_val <- tidied_val %>%
  filter(entry == "amour"| 
           entry == "espoir"| 
           entry == "haine"| 
           entry == "peur"| 
           entry == "tristesse"| 
           entry == "fer"| 
           entry == "sandwich"| 
           
           entry == "cauchemar"|
           entry =="douleur"| 
           entry =="rire"|
           entry =="passion"|
           entry =="jalousie"|
           entry == "racisme"| 
           entry == "anxiété"| 
           entry == "dent"| 
           
           entry == "plaisir"| 
           entry == "souffrance"| 
           entry == "colère"| 
           entry == "désagréable"| 
           entry == "bonheur"|
           entry == "richesse"| 
           entry == "poire"| 
           entry == "moyen"| 
         
           entry == "horreur"| 
           entry == "mensonge"| 
           entry == "confort"| 
           entry == "victoire"|
           entry == "diable"|
           entry == "chagrin"|
           entry == "vertu" |
           entry == "appareil") %>%
  group_by(ID)


readr::write_excel_csv(quality_val, "quality_val.csv") 

The ID variable was acquired by asking participants to enter it by themselves. I thought about whether it might be two different participants, on of whom accidentally put the wrong ID. But why would the two records have the same response time in that case?

May I know what you referred when saying “MD5 hash”? I’m wondering how to distinguish which four records belonged to that single participant…

Best wishes,
Chloris

[Chloris]

Hi Jeremy,

Thanks for your reply. Unfortunately, I cannot set the limit on the crowd-sourcing platform since one participant may or may not complete all the experiment sections (it’s free to choose).

I’m running into a new problem now – every time when I try to generate the results for downloading, it gets stuck at some point (e.g., “Downloading submissions (19500 rows…)”). I suppose it’s because of the big volume of data? Is there a way to fix this?

Thanks a lot!
Chloris

[Chloris]

For monitoring, I meant to know if there’s a way to figure out submission times for each experiment (and ideally for each group in each experiment) without downloading the results…

[Chloris]

Hi Jeremy,

I indeed meant the latter one. The code works perfectly. Thanks a lot!

Boyin

[Author]

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