Automated Author ProfileHulsmans, D.H.G.
Behavioural Science Institute, Radboud University0000-0003-3490-6356
Hulsmans, D.H.G.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 9.6 (sum of 5 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Three datasets described in manuscript are preprocessed data (imputed). One meta-data file for all (variables are the same), and R codes used for analyses can be found here. If you want to replicate main analyses of the findings, you can use the R script in 'Analyses_EMA_Data.html' and two pre-processed datasets: 'dfimp_smokers.csv' and 'dfimp_nonsmokers.csv'. The follow-up analyses were done on dataset dfimp_smokerswith.csv'. Please see 'Follow_up_Analyses_EMA_Data.html'. This should enable replication. R scripts from 'Preparation_descriptives_EMA_Data.html' were preparatory steps with some descriptive statistics on non-anonymized dataset that is not shared, this does provide some insight into construction and presented descriptives. Link to same and other materials is: https://doi.org/10.17605/OSF.IO/J2WQK
Authors
- Hulsmans, D.
Processed data (imputed and unimputed), meta-data, and R codes used for analyses can be found here.- If you want to replicate main analyses of the findings on between- and within-persons heterogeneity in idiographic networks, you can use pre-processed dataset 'df_networks_imputed.csv', with meta-data 'Metadata df_networks.docx'. Please see 'Script_Idiographic_network_analyses.html' which should enable replication of these main findings.- If you wish to replicate the SURPS profile attributions, please use 'Data_standardizedsurveys_wide_SURPS.csv'.- If you wish to replicate the imputation, please use 'df_networks_unimputed.csv'Both meta-data and R scripts for the latter two can be found on 'Metadata SURPS.docx' and 'Data_preparation.html' respectively.
Authors
- Hulsmans, D.H.G.
Processed data (imputed), meta-data, and R codes used for analyses can be found here. If you want to replicate main analyses of the findings, you can use pre-processed dataset 'data_case.csv', with meta-data 'meta_data_case.pdf'. Please see 'Rscript_case.html' which should enable replication of these main findings. Link to same and other scripts/materials=https://osf.io/xrmhu/?view_only=952d536450f44c64bcef661da3c4d7bd
Authors
- Hulsmans, Daan
Processed data, meta-data, and R code used for analyses can be found here.
Authors
- Hulsmans, D. H. G.