100+ datasets found
  1. t

    Yo-Yo Test Normative Data

    • topendsports.com
    Updated Oct 23, 2025
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    (2025). Yo-Yo Test Normative Data [Dataset]. https://www.topendsports.com/testing/norms/yo-yo.htm
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    Dataset updated
    Oct 23, 2025
    Variables measured
    Intermittent high-intensity aerobic capacity
    Measurement technique
    Yo-Yo Intermittent Recovery Test
    Description

    Fitness rating norms based on Bangsbo et al. (2008) formula and athlete performance data

  2. s

    Citation Trends for "Normative data for a solution-based taste test"

    • shibatadb.com
    Updated May 22, 2010
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    Yubetsu (2010). Citation Trends for "Normative data for a solution-based taste test" [Dataset]. https://www.shibatadb.com/article/xmYQRrhw
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    Dataset updated
    May 22, 2010
    Dataset authored and provided by
    Yubetsu
    License

    https://www.shibatadb.com/license/data/proprietary/v1.0/license.txthttps://www.shibatadb.com/license/data/proprietary/v1.0/license.txt

    Time period covered
    2011 - 2025
    Variables measured
    New Citations per Year
    Description

    Yearly citation counts for the publication titled "Normative data for a solution-based taste test".

  3. D

    Normative data

    • researchdata.ntu.edu.sg
    rar
    Updated May 29, 2020
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    Liang Phyllis; Wai Hang Kwong; Sidarta Ananda; Choon Kong Yap; Liang Phyllis; Wai Hang Kwong; Sidarta Ananda; Choon Kong Yap (2020). Normative data [Dataset]. http://doi.org/10.21979/N9/7VF22X
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    rar(182842674), rar(248768866), rar(246284247), rar(205035683), rar(288774835), rar(187435628), rar(201472991), rar(186882680), rar(192121535), rar(167687456)Available download formats
    Dataset updated
    May 29, 2020
    Dataset provided by
    DR-NTU (Data)
    Authors
    Liang Phyllis; Wai Hang Kwong; Sidarta Ananda; Choon Kong Yap; Liang Phyllis; Wai Hang Kwong; Sidarta Ananda; Choon Kong Yap
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Trials data for normative subjects.

  4. m

    Neuropsychology of language: Normative data for Verbal Repetition,...

    • data.mendeley.com
    Updated Apr 29, 2024
    + more versions
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    Estefanía Valcárcel Pestana (2024). Neuropsychology of language: Normative data for Verbal Repetition, Comprehension, Verbal Fluency & BNT indexes [Dataset]. http://doi.org/10.17632/p9gpnsdzx7.1
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    Dataset updated
    Apr 29, 2024
    Authors
    Estefanía Valcárcel Pestana
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset is a collaborative work for the subject "Neuropsychology of Language" taught at the Universidad Autónoma de Madrid, Spain (2023/2024 academic year). The aim is to determine the influence of age, years of education, and gender on four classic language assessment tasks: verbal repetition (subtest from the Test Barcelona Revisado; TBR), comprehension (subtest from the TBR), verbal fluency (COWAT and Isaacs Set-Test) and Boston Naming Test. Also, from the sample data, normative data in young and middle-aged adults can be obtained. For the application of the tests, the conventional instructions were followed, which can be consulted, for example, in Strauss et al. (2006). In addition to the sociodemographic variables above-mentioned, the following cognitive parameters are also included in the dataset: -Score for each item from the verbal repetition task -Total score for the verbal repetition task (range 0-60; a higher score means better performance) -Score for each item from the comprehension task -Total score for the comprehension task (range 0-16; a higher score means better performance) -Number of items correctly evoked in period 1-15" for each phonetic and semantic category -Number of items correctly evoked in the period 16-30" for each phonetic and semantic category -Number of items correctly evoked in the period 31-45" for each phonetic and semantic category -Number of items correctly evoked in the period 45-60" for each phonetic and semantic category -Number of items correctly evoked in the period 45-60" for each phonetic and semantic category -Total number of items correctly evoked 1-60" (sum of the above) for each phonetic and semantic category. -Total number of errors for each phonetic and semantic category -Total number of perseverations for each phonetic and semantic category -Total number of spontaneous hits in the BNT -Total number of hits after semantic clue in the BNT -Total number of hits after phonological clue in the BNT -Total number of hits after semantic clue in the BNT (sum of spontaneous hits + hits after semantic clue)

    *All authors contributed equally in this work

  5. f

    Table 1_Generating normative data from web-based administration of the...

    • frontiersin.figshare.com
    docx
    Updated Sep 20, 2024
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    Elizabeth Wragg; Caroline Skirrow; Pasquale Dente; Jack Cotter; Peter Annas; Milly Lowther; Rosa Backx; Jenny Barnett; Fiona Cree; Jasmin Kroll; Francesca Cormack (2024). Table 1_Generating normative data from web-based administration of the Cambridge Neuropsychological Test Automated Battery using a Bayesian framework.docx [Dataset]. http://doi.org/10.3389/fdgth.2024.1294222.s001
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    docxAvailable download formats
    Dataset updated
    Sep 20, 2024
    Dataset provided by
    Frontiers
    Authors
    Elizabeth Wragg; Caroline Skirrow; Pasquale Dente; Jack Cotter; Peter Annas; Milly Lowther; Rosa Backx; Jenny Barnett; Fiona Cree; Jasmin Kroll; Francesca Cormack
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    IntroductionNormative cognitive data can distinguish impairment from healthy cognitive function and pathological decline from normal ageing. Traditional methods for deriving normative data typically require extremely large samples of healthy participants, stratifying test variation by pre-specified age groups and key demographic features (age, sex, education). Linear regression approaches can provide normative data from more sparsely sampled datasets, but non-normal distributions of many cognitive test results may lead to violation of model assumptions, limiting generalisability.MethodThe current study proposes a novel Bayesian framework for normative data generation. Participants (n = 728; 368 male and 360 female, age 18–75 years), completed the Cambridge Neuropsychological Test Automated Battery via the research crowdsourcing website Prolific.ac. Participants completed tests of visuospatial recognition memory (Spatial Working Memory test), visual episodic memory (Paired Associate Learning test) and sustained attention (Rapid Visual Information Processing test). Test outcomes were modelled as a function of age using Bayesian Generalised Linear Models, which were able to derive posterior distributions of the authentic data, drawing from a wide family of distributions. Markov Chain Monte Carlo algorithms generated a large synthetic dataset from posterior distributions for each outcome measure, capturing normative distributions of cognition as a function of age, sex and education.ResultsComparison with stratified and linear regression methods showed converging results, with the Bayesian approach producing similar age, sex and education trends in the data, and similar categorisation of individual performance levels.ConclusionThis study documents a novel, reproducible and robust method for describing normative cognitive performance with ageing using a large dataset.

  6. t

    Plank Test Normative Data

    • mail.topendsports.com
    Updated Oct 9, 2025
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    (2025). Plank Test Normative Data [Dataset]. https://mail.topendsports.com/testing/tests/plank.htm
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    Dataset updated
    Oct 9, 2025
    Variables measured
    Core muscle endurance (seconds)
    Measurement technique
    Isometric forearm plank hold to failure
    Description

    Age and gender-specific norms for plank test performance based on Strand et al. (2014)

  7. f

    Normative data for VO2 max of men.

    • datasetcatalog.nlm.nih.gov
    Updated Jul 30, 2018
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    Li, Qian; Buford, Thomas W.; Modave, François; Guo, Yi; Rosenberg, Eric I.; Vincent, Heather K.; Bian, Jiang; Leavitt, Trevor; Smith, Megan D. (2018). Normative data for VO2 max of men. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000610837
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    Dataset updated
    Jul 30, 2018
    Authors
    Li, Qian; Buford, Thomas W.; Modave, François; Guo, Yi; Rosenberg, Eric I.; Vincent, Heather K.; Bian, Jiang; Leavitt, Trevor; Smith, Megan D.
    Description

    Normative data for VO2 max of men.

  8. f

    Data from: Normative data for executive function tests in an Ecuadorian...

    • datasetcatalog.nlm.nih.gov
    • tandf.figshare.com
    Updated Jul 1, 2024
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    Arango-Lasprilla, Juan Carlos; Arjol, David; Olabarrieta-Landa, Laiene; Christ, Bryan R.; Perrin, Paul B.; Rivera, Diego; Bósquez, María José Fierro (2024). Normative data for executive function tests in an Ecuadorian Waranka minority population [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0001488648
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    Dataset updated
    Jul 1, 2024
    Authors
    Arango-Lasprilla, Juan Carlos; Arjol, David; Olabarrieta-Landa, Laiene; Christ, Bryan R.; Perrin, Paul B.; Rivera, Diego; Bósquez, María José Fierro
    Description

    Objective: To generate normative data (ND) for executive functions tests in the Waranka minority population of Ecuador. Method: Four-hundred participants aged 6–17 completed the Symbol-Digit Modalities Test (SDMT), Trail-Making Test (TMT), Modified-Wisconsin Card Sorting Test (M-WCST), and Test of Colors-Words (STROOP). Scores were normed using multiple linear regressions, including age, age2, natural logarithm of mean parent education (MPE), sex, bilingualism, and two-way interactions as predictors. Results: Age by MPE and Age2 by MPE interactions arose for SDMT, so that children with illiterate parents scored lower than those with literate parents. Girls scored higher in SDMT. All TMT and M-WCST scores were influenced by age2. Age by MPE interaction was found for TMT–A, so that children with higher MPE went faster; and age by bilingualism interaction for TMT–B, so that more bilingual children needed less time. Stroop-Word and Color were influenced by age2 by MPE interaction, so that children, while older, scored higher, especially those with higher MPE. Also, age2 by sex interaction arose, so that girls increased scores curvilinearly while boys linearly. Word-Color was influenced by age, while Stroop-interference by age2. Age by MPE interaction was found for MCST-Categories and Perseveration, so that perseverations decreased to then increased, especially in those with illiterate parents. M-WCST-Category scores increased to then decrease later on age in children with illiterate parents. Z-scores calculated through indigenous ND were significantly lower than generated through non-indigenous norms. Conclusions: ND for minority populations are critical since Waranka sample performed worse when using non-indigenous norms for z-score calculation.

  9. f

    Data from: Phonological awareness and early reading and writing abilities in...

    • datasetcatalog.nlm.nih.gov
    • scielo.figshare.com
    Updated Mar 27, 2019
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    Dias, Natália Martins; León, Camila Barbosa Riccardi; Almeida, Ágata; de Cássia Batista Pazeto, Talita; Seabra, Alessandra Gotuzo; Zauza, Grace; Lira, Sandra (2019). Phonological awareness and early reading and writing abilities in early childhood education: preliminary normative data [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000163631
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    Dataset updated
    Mar 27, 2019
    Authors
    Dias, Natália Martins; León, Camila Barbosa Riccardi; Almeida, Ágata; de Cássia Batista Pazeto, Talita; Seabra, Alessandra Gotuzo; Zauza, Grace; Lira, Sandra
    Description

    ABSTRACT Objective: to provide preliminary normative data for the Reading and Writing Test by type of school, and normative data for the Phonological Awareness Test by Oral Production for private schools and update their normative data available for public schools, all of which are for children in the final year of early childhood education. Methods: 267 children, in the age range of 5 years, and typical development. Identification Questionnaire for Parents, Phonological Awareness Test by Oral Production and Reading and Writing Test were used. The means of performance in the tests of the present sample were compared with the existing normative data to justify normative data provision and updating. Results: Student’s t-test revealed that the private school children outperformed those of the public schools in all measures, reinforcing the need for specific standards, according to the type of school. There were strong to very strong relationships among the variables evaluated, demonstrating a marked association between phonological awareness and initial reading and writing abilities. The Wilcoxon test revealed significant differences between the performance of the children of the present study, from both private and public schools, and the data from the Phonological Awareness Test by Oral Production standardization sample, suggesting the need to update the Phonological Awareness Test by Oral Production standards. Finally, the new normative data were presented. Conclusion: the need to make available and update the test standards used, according to the type of school, was confirmed. Further studies are necessary to expand the data presented to other age groups.

  10. f

    Flemish normative data for the Buschke selective reminding test_Data

    • datasetcatalog.nlm.nih.gov
    • figshare.com
    Updated Dec 28, 2018
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    Huybrechts, Sophie; Gillebert, Céline R.; Thielen, Hella; Verleysen, Gregory; Lafosse, Christophe (2018). Flemish normative data for the Buschke selective reminding test_Data [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000723767
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    Dataset updated
    Dec 28, 2018
    Authors
    Huybrechts, Sophie; Gillebert, Céline R.; Thielen, Hella; Verleysen, Gregory; Lafosse, Christophe
    Description

    This dataset was used to acquire normative data for a Flemish version of the Buschke selective reminding test (SRT). Data was obtained in 3257 neurologically healthy adults (age range: 18-94 years old). The influences of age, sex and educational level on SRT performance were analysed using robust regression. This study gained ethical approval from the Social and Societal Ethics Committee of the KU Leuven (reference number: G-2018 11 1388).

  11. d

    Establishment of Age-Specific Normative Data for Auditory Brainstem Response...

    • dataone.org
    • dataverse.harvard.edu
    Updated Nov 8, 2023
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    Camarillo, Ed Levi (2023). Establishment of Age-Specific Normative Data for Auditory Brainstem Response Wave Measurement and its Application for Hearing Loss Diagnosis in a Tertiary Government Hospital [Dataset]. http://doi.org/10.7910/DVN/VOMUKT
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    Camarillo, Ed Levi
    Description

    The primary purpose of this study is to obtain ABR recordings, create normative ABR values for infants seen at SPMC, and compare the values to published data.

  12. f

    Normative data for reaction time tests.

    • datasetcatalog.nlm.nih.gov
    • plos.figshare.com
    Updated Nov 22, 2021
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    Snapp, Hillary; Braverman, Alexandr; Kiderman, Alexander; Balaban, Carey D.; Ashmore, Robin C.; Hoffer, Michael; Mazur, Christian; Williams, Erin; Crawford, James; Kullmann, Aura; Szczupak, Mikhaylo; Murphy, Sara; Marshall, Kathryn (2021). Normative data for reaction time tests. [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000874159
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    Dataset updated
    Nov 22, 2021
    Authors
    Snapp, Hillary; Braverman, Alexandr; Kiderman, Alexander; Balaban, Carey D.; Ashmore, Robin C.; Hoffer, Michael; Mazur, Christian; Williams, Erin; Crawford, James; Kullmann, Aura; Szczupak, Mikhaylo; Murphy, Sara; Marshall, Kathryn
    Description

    Normative data for reaction time tests.

  13. t

    Stork Balance Test Methodology

    • topendsports.com
    Updated Nov 21, 2025
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    (2025). Stork Balance Test Methodology [Dataset]. https://www.topendsports.com/testing/tests/balance-stork.htm
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    Dataset updated
    Nov 21, 2025
    Variables measured
    Single-leg balance duration on ball of foot
    Measurement technique
    Timed balance hold until form breakdown occurs
    Description

    Scientific basis and normative data for single-leg balance assessment in athletic populations

  14. D

    Data from: Normative data on Dutch idiomatic expressions: Native speakers

    • ssh.datastations.nl
    csv, pdf, txt, zip
    Updated Nov 2, 2023
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    F.C.W. Hubers; W. van Ginkel; C. Cucchiarini; H. Strik; A.F.J. Dijkstra; F.C.W. Hubers; W. van Ginkel; C. Cucchiarini; H. Strik; A.F.J. Dijkstra (2023). Normative data on Dutch idiomatic expressions: Native speakers [Dataset]. http://doi.org/10.17026/DANS-ZJX-HNSK
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    txt(43321), zip(20928), pdf(139247), csv(43327), pdf(160884)Available download formats
    Dataset updated
    Nov 2, 2023
    Dataset provided by
    DANS Data Station Social Sciences and Humanities
    Authors
    F.C.W. Hubers; W. van Ginkel; C. Cucchiarini; H. Strik; A.F.J. Dijkstra; F.C.W. Hubers; W. van Ginkel; C. Cucchiarini; H. Strik; A.F.J. Dijkstra
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    In the context of the research programme ‘Idiomatic Second Language Acquisition’ (for more information see http://isla.ruhosting.nl), we collected normative data of 374 Dutch idiomatic expressions by 390 native speakers. In an online test, we asked participants to judge various dimensions of idiomatic expressions on a five-point scale: Frequency, Usage, Familiarity, Imageability, and Transparency. In addition, we objectively assessed their knowledge of idiom meaning by means of a multiple choice question (Idiom knowledge recognition). The dataset contains the aggregated results per expression for the 5 subjective dimensions (Frequency, Usage, Familiarity, Imageability, and Transparency) and the objective Idiom knowledge recognition (proportion correct).This work is part of the research program Free Competition in the Humanities with project number 23000349 NWO ISLA FdL, which is financed by the Netherlands Organisation for Scientific Research (NWO).

  15. r

    Multicenter normative data for mesopic microperimetry

    • researchdata.edu.au
    Updated 2024
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    Zhichao Wu; Fred K. Chen; Kristina Pfau; Georg Ansari; Philipp L. Mueller; Leon von der Emde; Jason Charng; Jasleen K Jolly; Maximilian Pfau; Centre for Ophthalmology and Visual Science (2024). Multicenter normative data for mesopic microperimetry [Dataset]. http://doi.org/10.5281/ZENODO.13625812
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    Dataset updated
    2024
    Dataset provided by
    The University of Western Australia
    Zenodo
    Authors
    Zhichao Wu; Fred K. Chen; Kristina Pfau; Georg Ansari; Philipp L. Mueller; Leon von der Emde; Jason Charng; Jasleen K Jolly; Maximilian Pfau; Centre for Ophthalmology and Visual Science
    Description

    This record contains the analysis and underlying data presented in the manuscript Pfau et al. 'Multicenter normative data for mesopic microperimetry'.

    Contents: 2024-08-30_Multicenter-Normal-Data.csv: Newly published normal data for mesopic microperimetry 2024-08-30_Analysis.R: Analysis script 2024-08-30_Vignette-to-create-normal-data.R: Software example to create normative maps

    The subfolders Figures and Tables show the analysis results. The folder Intermediary_Results contains the results of the cross-validation folds to assess model performance.

    To run the analysis code in 2024-08-30_Analysis.R, the following data is needed in addition: Astle et al. Data Brief. 2016 Aug 4;9:673-675. doi: 10.1016/j.dib.2016.07.061

    The 2024-08-30_Multicenter-Normal-Data.csv file with the data contains the following columns: source: Describes the clinical site MachineID: ID of the MAIA device used for data collection ParticipantID: ID of the participant EID: ID of the eye eye: Laterality (either Right or Left) sex: Sex (f for female, m for male) age: Age in years ExamID: ID of the exam ExamBaselineID: ID of the corresponding baseline exam (-1 indicates that the exam itself is the baseline exam) GridUsed: Name of the grid falsepos: Rate of false positive responses to Heijl-Krakau stimulus presentations to the optic nerve head (blind spot) bcea63_area_deg2: Fixation stability in terms of the bivariate contour ellipse area covering 63% of the fixation points (in square degree) bcea95_area_deg2: Fixation stability in terms of the bivariate contour ellipse area covering 95% of the fixation points (in square degree) pointID: ID of the test point eccentricity: Eccentricity of the test point (in degree) x_coord: X-coordinate of the test point (in degree), negative values are temporal to the fovea and positive values are nasal to the fovea (in retinal space) y_coord: Y-coordinate of the test point (in degree), negative values are inferior to the fovea and positive values are superior to the fovea (in retinal space) sensitivity: Sensitivity at the test point (in dB)

  16. H

    Data from: Developmental Normative Data of the Rey-Osterrieth Complex Figure...

    • dataverse.harvard.edu
    Updated May 3, 2019
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    Mostafa Eldeib (2019). Developmental Normative Data of the Rey-Osterrieth Complex Figure Test in an Egyptian Population [Dataset]. http://doi.org/10.7910/DVN/8MPQGI
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 3, 2019
    Dataset provided by
    Harvard Dataverse
    Authors
    Mostafa Eldeib
    License

    https://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/8MPQGIhttps://dataverse.harvard.edu/api/datasets/:persistentId/versions/1.0/customlicense?persistentId=doi:10.7910/DVN/8MPQGI

    Area covered
    Egypt
    Description

    excel file contains numerical data for peer-reviewed

  17. u

    Age dependent computerized rotational head impulse test (crHIT)

    • researchdata.up.ac.za
    xlsx
    Updated Jun 2, 2023
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    Mangelique du Plessis; Barbara Heinze; Alexander Kiderman; Jorge Gonzales; Tarryn Reddy (2023). Age dependent computerized rotational head impulse test (crHIT) [Dataset]. http://doi.org/10.25403/UPresearchdata.22087520.v1
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    xlsxAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    University of Pretoria
    Authors
    Mangelique du Plessis; Barbara Heinze; Alexander Kiderman; Jorge Gonzales; Tarryn Reddy
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This dataset determines the normative Vestibulo–ocular reflex (VOR) gain output values of the computerized rotational head impulse test (crHIT) with stationary visual targets (earthbound) in healthy participants. Participants were recruited using convenience sampling and assessed with the crHIT using stationary targets. The data consist of the folowing sheets: Sheet one: demographics of the participant population Sheet two: correlation coefficient between test, age and gender Sheet three: Linear regression analysis Sheet four: crHITgain output combined for leftward and rightward rotation Sheet five: 95% Confidence interval

  18. s

    Citation Trends for "Some Normative Data for the Spiral Aftereffect"

    • shibatadb.com
    Updated Aug 15, 1970
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    Yubetsu (1970). Citation Trends for "Some Normative Data for the Spiral Aftereffect" [Dataset]. https://www.shibatadb.com/article/A5ShqHSk
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    Dataset updated
    Aug 15, 1970
    Dataset authored and provided by
    Yubetsu
    License

    https://www.shibatadb.com/license/data/proprietary/v1.0/license.txthttps://www.shibatadb.com/license/data/proprietary/v1.0/license.txt

    Time period covered
    1974 - 1985
    Variables measured
    New Citations per Year
    Description

    Yearly citation counts for the publication titled "Some Normative Data for the Spiral Aftereffect".

  19. Normative Data Dutch Oxford Cognitive Screen (OCS-NL)

    • figshare.com
    • datasetcatalog.nlm.nih.gov
    txt
    Updated Jul 2, 2019
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    Hanne Huygelier; Brenda Schraepen; Nele Demeyere; Céline R. Gillebert (2019). Normative Data Dutch Oxford Cognitive Screen (OCS-NL) [Dataset]. http://doi.org/10.6084/m9.figshare.8428895.v1
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    txtAvailable download formats
    Dataset updated
    Jul 2, 2019
    Dataset provided by
    Figsharehttp://figshare.com/
    figshare
    Authors
    Hanne Huygelier; Brenda Schraepen; Nele Demeyere; Céline R. Gillebert
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    These files contain all data files of the OCS-NL normative study.

  20. f

    Data_Sheet_1_The Chinese Brief Cognitive Test: Normative Data Stratified by...

    • datasetcatalog.nlm.nih.gov
    • frontiersin.figshare.com
    Updated Jul 4, 2022
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    Shi, Chuan; Li, Tao; Wu, Renrong; Xu, Yong; Li, Yi; Li, Nan; Peng, Min; Wang, Xijin; Zou, Shaohong; Ye, Shuling; Xu, Xiufeng; Guo, Wanjun; Zhu, Gang; Cheng, Yuqi; Liu, Dengtang; Liu, Huanzhong; Hu, Shaohua; Wang, Huaning; Yang, Juan; Xie, Mengjuan; Yu, Xin (2022). Data_Sheet_1_The Chinese Brief Cognitive Test: Normative Data Stratified by Gender, Age and Education.xlsx [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000294030
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    Dataset updated
    Jul 4, 2022
    Authors
    Shi, Chuan; Li, Tao; Wu, Renrong; Xu, Yong; Li, Yi; Li, Nan; Peng, Min; Wang, Xijin; Zou, Shaohong; Ye, Shuling; Xu, Xiufeng; Guo, Wanjun; Zhu, Gang; Cheng, Yuqi; Liu, Dengtang; Liu, Huanzhong; Hu, Shaohua; Wang, Huaning; Yang, Juan; Xie, Mengjuan; Yu, Xin
    Description

    The aim of this study was to develop a brief version of cognitive assessment test for evaluating the efficacy of treatments targeting cognitive impairments in Chinese schizophrenia patients, to examine its reliability, and establish normative data. Stratified according to age, gender, and educational level, healthy adult subjects were recruited from fifteen institutions in seven administrative regions of China and 723 valid samples were obtained, of which 50 were retested. Generalized Linear Models were conducted to analyze the effects of age, sex, and education. There was no significant difference between genders, while significant effects were demonstrated respectively among age and education on the normative data of C-BCT. The Cronbach α of C-BCT is 0.75, and the test-retest reliability (ICC) ranged from 0.62 to 0.76. Normative data of C-BCT were generated by gender, age and education, and the effects of these demographic factors were analyzed. It revealed good internal consistency and test-retest reliability of C-BCT.

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(2025). Yo-Yo Test Normative Data [Dataset]. https://www.topendsports.com/testing/norms/yo-yo.htm

Yo-Yo Test Normative Data

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5 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Oct 23, 2025
Variables measured
Intermittent high-intensity aerobic capacity
Measurement technique
Yo-Yo Intermittent Recovery Test
Description

Fitness rating norms based on Bangsbo et al. (2008) formula and athlete performance data

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