Tim Draws

2.1k citations
28 papers · 1.4k · 2 hit papers · h-index 13

Impact in

Papers in

Tim Draws

28 papers receiving 1.4k citations

Tim Draws's Hit Papers

A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP 2020 · 212 citations
2120+2+4Years since publication250500750

Peers

Tim Draws
Comparison fields: 5 of 96
  • Cognitive Neuroscience 247
  • Statistics and Probability 73
  • Information Systems 144
  • Safety Research 48
  • General Decision Sciences 11
Replace Hu Chuan-Peng with:
Hu Chuan-Peng China
Sangsuk Yoon United States
Jiří Lukavský Czechia
Jan Gerrit Voelkel United States
Sam Parsons United Kingdom
Martin E. Arendasy Austria
Olivia Guest Netherlands
Μαριέττα Παπαδάτου-Παστού Greece
Tiago Bortolini Brazil
Nina Lauharatanahirun United States
Tim Draws relative to Hu Chuan-Peng China Hu Chuan-Peng's profile →
Citations per field
00.5×2×3×3.7×
Hu Chuan-Peng · 1×
Citations per year

Countries citing papers authored by Tim Draws

Since Specialization
Citations

This map shows the geographic impact of Tim Draws's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Tim Draws with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Draws more than expected).

Fields of papers citing papers by Tim Draws

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tim Draws. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Tim Draws. The network helps show where Tim Draws may publish in the future.

Co-authors

The 25 scholars most cited alongside Tim Draws, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tim Draws Line = papers co-authored together Tim Draws links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The JASP guidelines for conducting and reporting a Bayesian analysis
Hit paper breakdown →
2020779
2
A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP
Hit paper breakdown →
2020212
3 202167
4 202359
5 202252
6 202141
7 202130
8 202125
9 202224
10 202219
11 202218
12 202316
13 202314
14 202312
15 202110
16 202310
17 20218
18 20238
19 20207
20 20237

About Tim Draws

Tim Draws is a scholar working on Information Systems, Safety Research, Statistics and Probability, Computer Science Applications and Sociology and Political Science, having authored 28 papers that have together received 1.4k indexed citations. Recurring topics across this work include Information Retrieval and Search Behavior (8 papers), Ethics and Social Impacts of AI (6 papers), Statistical Methods and Bayesian Inference (3 papers), Recommender Systems and Techniques (2 papers), Sentiment Analysis and Opinion Mining (2 papers), Privacy, Security, and Data Protection (1 paper), Religion, Spirituality, and Psychology (1 paper) and Mobile Crowdsensing and Crowdsourcing (1 paper). The work is most often cited by research in Cognitive Neuroscience (247 citations), Statistics and Probability (73 citations), Information Systems (144 citations), Safety Research (48 citations) and General Decision Sciences (11 citations). Tim Draws has collaborated with scholars based in Netherlands, United States and Switzerland. Frequent co-authors include Nava Tintarev, Jan Gerrit Voelkel, Koen Derks, Max Hinne, Dóra Matzke, Šimon Kucharský, Alexandra Sarafoglou, Johnny B. van Doorn, Maarten Marsman and Eric‐Jan Wagenmakers. Their work appears in journals such as User Modeling and User-Adapted Interaction, Patterns, Religion Brain & Behavior, ACM Transactions on the Web and Psychonomic Bulletin & Review.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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