personality_handwriting__graphology
10,050 responses from 402 respondents to 25 items.
About this table
| Description | Binary expert-rated handwriting features (25 items, 0/1; N=402). |
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| Reference | Thomas S (2026). Data for understanding personality and financial behaviour using handwriting. Harvard Dataverse. https://doi.org/10.7910/DVN/2IBLRK |
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| Licence | CC0 1.0 |
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| Source data | https://doi.org/10.7910/DVN/2IBLRK |
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Size and shape
| Responses | 10,050 |
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| Respondents | 402 |
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| Items | 25 |
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| Response categories | 2 |
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| Responses per respondent | 25 |
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| Responses per item | 402 |
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| Density | 1 |
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| Longitudinal | FALSE |
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Classification
| measurement tool | Observational rating |
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| item format | Likert Scale/selected response |
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Item text
This table has item text in the IRW: the wording administered to respondents, not just the response codes.
| Instrument | Personality and Financial Behaviour Questionnaire (Thomas, Parul University) - Handwriting Traits checklist (neuroticism indicators) |
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| Mean words per item | 4.480 |
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| Mean characters per item | 26 |
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| Mean characters per response | 2.500 |
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| Flesch-Kincaid grade level | 4.355 |
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Get the data
Or load it directly in R or Python:
# R
install.packages("remotes")
remotes::install_github("itemresponsewarehouse/Rpkg")
library(irw)
df <- irw_fetch("personality_handwriting__graphology")
# Python
pip install irw
import irw
df = irw.fetch("personality_handwriting__graphology")
Version and provenance
| IRW version | v393 |
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| Redivis dataset | item_response_warehouse_2 v19.0 |
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| Redivis dataset DOI | 10.57761/qtx5-4m80 |
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| Manifest pin for this IRW version | v19.0 |
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| Metadata source | irw_meta v23.0 |
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