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TwitterFitness rating norms based on Bangsbo et al. (2008) formula and athlete performance data
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Yearly citation counts for the publication titled "Normative data for a solution-based taste test".
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Trials data for normative subjects.
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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
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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.
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TwitterAge and gender-specific norms for plank test performance based on Strand et al. (2014)
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TwitterNormative data for VO2 max of men.
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TwitterObjective: 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.
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TwitterABSTRACT 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.
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TwitterThis 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).
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TwitterThe 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.
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TwitterNormative data for reaction time tests.
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TwitterScientific basis and normative data for single-leg balance assessment in athletic populations
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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).
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TwitterThis 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)
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excel file contains numerical data for peer-reviewed
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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
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Yearly citation counts for the publication titled "Some Normative Data for the Spiral Aftereffect".
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These files contain all data files of the OCS-NL normative study.
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TwitterThe 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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TwitterFitness rating norms based on Bangsbo et al. (2008) formula and athlete performance data