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Hypothesizing after the results are known (HARKing) (section Hypothesizing after the results are known (HARKing))
such as preregistration aim to reduce HARKing and differentiates pure HARKing from transparent forms of HARKing that are not necessarily detrimental to

11 KB (1,637 words) - 12:08, 19 May 2022
Data driven hypotheses without disclosure (‘HARKing’) (section Data driven hypotheses without disclosure (‘HARKing’))
rationale behind it. HARKing is considered to be a detrimental research practice. This thematic page will try to address the logic behind HARKing and hopefully

5 KB (769 words) - 17:42, 26 March 2021
Using data not created for research purposes in the context of collaboration with private companies
scenario include: data reuse, replicability of results conflicts of interests, HARKing, informed consent, honesty in communication of results, reliability of data

1 KB (118 words) - 15:33, 4 November 2021
Research Procedures and Research Integrity: An Educational Scenario by the EnTIRE project
Hypothesizing after the results ('HARKing'); P-hacking; Selection bias; University procedures, processes and guidelines to address HARKing, P-hacking and selection

4 KB (407 words) - 15:20, 19 October 2021
Theme
disclosure (‘HARKing’) Duplicate publications and secondary publications Funding (Sponsorship) bias Hypothesizing after the results are known (HARKing) Improper

215 members (0 subcategories, 0 files) - 17:08, 28 November 2023
Theme
disclosure (‘HARKing’) Duplicate publications and secondary publications Funding (Sponsorship) bias Hypothesizing after the results are known (HARKing) Improper

31 KB (1,783 words) - 15:37, 14 February 2024
Collaborative Working Between Academia and Industry: An Educational Scenario by the EnTIRE project
of Interest between academia and industry; Data usage and data privacy; HARKing (Hypothesizing after the results are known); Preregistration of studies;

5 KB (466 words) - 15:21, 19 October 2021
Maintenance:ExportThemesRelated
pre-registration Replicability Data driven hypotheses without disclosure (‘HARKing’) Replicability in the Humanities Replicability Hidden for a century, 'fake'

112 bytes (0 words) - 12:15, 26 October 2020
Statistical pre-registration
yet they report their study as exploratory or hypothesis-generating (see HARKing thematic page). Observing the data before choosing which statistical tests

7 KB (970 words) - 22:10, 24 October 2020
Non-disclosure of changes to the research design
contribution was Oct 27, 2020 Data driven hypotheses without disclosure (‘HARKing’) P-value hacking AllTrials campaign Honesty Reliability

3 KB (407 words) - 22:54, 27 October 2020
Inappropriate study design
2021 Education Open About Data driven hypotheses without disclosure (‘HARKing’) P-value hacking Keeping inadequate notes of the research process Objectivity

3 KB (397 words) - 17:56, 26 March 2021
Questionable Research Practices in Analysis and Reporting
reporting include: Report on data driven hypotheses without disclosure [‘HARKing’ ‐ Hypothesizing After Results are Known ‐ typically with a view to make

4 KB (556 words) - 10:06, 28 October 2020
Publication bias (positive results)
About Education Open About Data driven hypotheses without disclosure (‘HARKing’) Non-reporting of negative findings Instruction:312681e3-96e5-4ebe-85f7-6fa2947d1f4a

4 KB (533 words) - 11:42, 27 March 2021
Preregistration of animal study protocols
hypotheses and statistical plans, preregistration reduces misconducts like HARKing (Hypothesis After Results are Known) and p-hacking. The free access of study

5 KB (618 words) - 17:49, 14 July 2021
Improper data use (a bias distorting research results)
Open About P-value hacking Data driven hypotheses without disclosure (‘HARKing’) Accuracy Questionable research practice

4 KB (549 words) - 21:44, 1 February 2021
Questionable research practices & research misbehaviors
reporting, examples of QRPs are hypothesizing after the results are known (HARKing), concealing results that contradict earlier findings, or not publishing

5 KB (632 words) - 14:42, 20 March 2022
Replicability
contribution was Oct 21, 2020 Data driven hypotheses without disclosure (‘HARKing’) Brian Nosek Michèle B Nuijten Edward Diener John Ioannidis Reliability

7 KB (1,058 words) - 12:17, 21 October 2020
Inferring from P-values
Open About Cases Open About Data driven hypotheses without disclosure (‘HARKing’) P-value hacking Statistical pre-registration Leo Kennedy-Shaffer Ronald

7 KB (996 words) - 22:05, 9 February 2023
Research Integrity and Research Ethics Scenarios for Teaching
Data sharing Experimental design Fabrication Falsification Good Practice HARKing Harm Institutional Responsibilities International collaboration Journal

6 KB (646 words) - 15:24, 22 October 2021
Resource
PracticeGovernanceGrant applicationsGrant applicationsGraph manipulationHARKingHandling Social MediaHandling of dataHarmHazardous substancesHealthHonorary

31 KB (6,324 words) - 15:37, 14 February 2024