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About 10,000 papers for “Predictive validity”

Predictive validity.

Roberta Maria Lorenzi (16920886), Alice Geminiani (6036272), Yann Zerlaut (3926813) et al. · Figshare · 2023

<p>Mean-field simulations using different strengths at PC connections. Simulations last 500 ms with a time resolution of 0.1 ms and <i>υ</i>drive is a step at 50 Hz lasting 250 ms starting at 125 ms. Quantitative score normalized to baseline (w = 100% in blue). <b>A) MLI-PC feed forward inhibition</b>. The change of total activity (measured as Area Under Curve (AUC)) and the initial peak amplitude decrease exponentially with the MLI-PC strength. The amplitude of the pause after the peak response decreases with MLI-PC strength following an inverse sigmoidal function. <b>B) PC Learning</b> with different GrC-PC plasticity conditions (Long Term Potentiation (LTP) and Long Term Depression (LTD)). AUC linearly increases with the GrC-PC strength, matching the experimental values in experimental learning protocols. The initial peak caused by the step stimulus onset increases with GrC-PC until saturation, following a sigmoidal function.</p>

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Predictive validity

Sevenster, Anneline · Leiden Repository (Leiden University) · 2019

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Posterior Predictive Validity.

Lara Henco (9124477), Andreea O. Diaconescu (9443979), Juha M. Lahnakoski (9187387) et al. · Figshare · 2020

<p>Simulated Behavior from the posterior estimates of all participants, revealed the same effects as real behavior: Boxes mark 95% confidence intervals and vertical lines standard deviations.</p> <p>(TIF)</p>

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Predictive Validity Analysis.

Kate E. Mooney (11785899), Charlie Welch (6285863), Gareth Palliser (20903089) et al. · Figshare · 2025

<div> The routine measurement of children’s developmental health varies across educational settings and systems. The Early Years Foundation Stage Profile (EYFSP) is a routinely recorded measure of a child’s development completed at the end of their first school year, for all children attending school in England and Wales. Despite widespread use for research and educational purposes, the measurement properties are unknown. This study examined the internal consistency and structural validity of the EYFSP, investigating whether the summed item-level scores, which we refer to as the ‘total score’, can be used as a summary of children’s developmental health. It also examined predictive validity of the total score with respect to later academic attainment and behavioural, social, and emotional difficulties. The data source was the longitudinal prospective birth cohort, Born in Bradford (BiB), and routine education data were obtained from Local Authorities. The internal consistency and structural validity of the EYFSP total score were investigated using Confirmatory Factor Analysis and a Rasch model. Predictive validity was assessed using linear mixed effects models for Key Stage 2 (Maths, Reading, Grammar/Punctuation/Spelling), and behavioural, social, and emotional difficulties (Strengths and Difficulties Questionnaire). We found that the EYFSP items demonstrated internal consistency, however, an Item Response model suggested weak structural validity (n = 10,589). Mixed effects regression found the EYFSP total score to predict later academic outcomes (n = 2711), and behavioural, social, and emotional difficulties (n = 984). This study has revealed that whilst caution should be applied for measurement of children with close to ‘average’ ability levels using the EYFSP, the EYFSP total score is an internally consistent measure with predictive validity. </div>

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Predictive Validity Data Set

Antonio Abeyta · Figshare · 2022

Verbal and Quantitative Reasoning GRE scores and percentiles were collected by querying the student database for the appropriate information. Any student records that were missing data such as GRE scores or grade point average were removed from the study before the data were analyzed. The GRE Scores of entering doctoral students from 2007-2012 were collected and analyzed. A total of 528 student records were reviewed. Ninety-six records were removed from the data because of a lack of GRE scores. Thirty-nine of these records belonged to MD/PhD applicants who were not required to take the GRE to be reviewed for admission. Fifty-seven more records were removed because they did not have an admissions committee score in the database. After 2011, the GRE’s scoring system was changed from a scale of 200-800 points per section to 130-170 points per section. As a result, 12 more records were removed because their scores were representative of the new scoring system and therefore were not able to be compared to the older scores based on raw score. After removal of these 96 records from our analyses, a total of 420 student records remained which included students that were currently enrolled, left the doctoral program without a degree, or left the doctoral program with an MS degree. To maintain consistency in the participants, we removed 100 additional records so that our analyses only considered students that had graduated with a doctoral degree. In addition, thirty-nine admissions scores were identified as outliers by statistical analysis software and removed for a final data set of 286 (see <b>Outliers</b> below). <b>Outliers</b><b> </b>We used the automated ROUT method included in the PRISM software to test the data for the presence of outliers which could skew our data. The false discovery rate for outlier detection (Q) was set to 1%. After removing the 96 students without a GRE score, 432 students were reviewed for the presence of outliers. ROUT detected 39 outliers that were removed before statistical analysis was performed. <b>Sample</b><b> </b>See detailed description in the <i>Participants </i>section. Linear regression analysis was used to examine potential trends between GRE scores, GRE percentiles, normalized admissions scores or GPA and outcomes between selected student groups. The D’Agostino &amp; Pearson omnibus and Shapiro-Wilk normality tests were used to test for normality regarding outcomes in the sample. The Pearson correlation coefficient was calculated to determine the relationship between GRE scores, GRE percentiles, admissions scores or GPA (undergraduate and graduate) and time to degree. Candidacy exam results were divided into students who either passed or failed the exam. A Mann-Whitney test was then used to test for statistically significant differences between mean GRE scores, percentiles, and undergraduate GPA and candidacy exam results. Other variables were also observed such as gender, race, ethnicity, and citizenship status within the samples. <i>Predictive Metrics. </i>The input variables used in this study were GPA and scores and percentiles of applicants on both the Quantitative and Verbal Reasoning GRE sections. GRE scores and percentiles were examined to normalize variances that could occur between tests. <i>Performance Metrics. </i>The output variables used in the statistical analyses of each data set were either the amount of time it took for each student to earn their doctoral degree, or the student’s candidacy examination result.

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Predictive validity of EWWS.

Amy L. Bartels (6635681), Suzanne J. Peterson (6635684), Christopher S. Reina (6635687) · Figshare · 2019

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Predictive validity of measures.

David Lacko (10681349), Tomáš Prošek (16324880), Jiří Čeněk (9647857) et al. · Figshare · 2023

&lt;div&gt;&lt;p&gt;Cognitive styles are commonly studied constructs in cognitive psychology. The theory of field dependence-independence was one of the most important cognitive styles. Yet in the past, its measurement had significant shortcomings in validity and reliability. The theory of analytic and holistic cognitive styles attempted to extend this theory and overcome its shortcomings. Unfortunately, the psychometric properties of its measurement methods were not properly verified. Furthermore, new statistical approaches, such as analysis of reaction times, have been overlooked by current research. The aim of this pre-registered study was to verify the psychometric properties (i.e., factor structure, split-half reliability, test-retest reliability, discriminant validity with intelligence and personality, and divergent, concurrent and predictive validity) of several methods routinely applied in the field. We developed/adapted six methods based on self-report questionnaires, rod-and-frame principles, embedded figures, and hierarchical figures. The analysis was conducted on 392 Czech participants, with two data collection waves. The results indicate that the use of methods based on the rod-and-frame principle may be unreliable, demonstrating no absence of association with intelligence. The use of embedded and hierarchical figures is recommended. The self-report questionnaire used in this study showed an unsatisfactory factor structure and also cannot be recommended without futher validation on independent samples. The findings also did not correspond with the original two-dimensional theory.&lt;/p&gt;&lt;/div&gt;

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Study 3b: predictive validity

FRIEDRICH, Théo, Boudjemadi, Valerian, Bruno, CHAUVIN · Open Science Framework · 2024

The general objective of this study aims to reduce ageism by acting on it and its determinants. Based on Intergroup Contact Theory (Allport, 1954) and Intergroup Threat Theory (Stephan &amp; Stephan, 2017), we hypothesize that the relationship between intergenerational contacts and prescriptive stereotypes of ageism (North &amp; Fiske, 2012) is mediated by the threats elicited by older people.

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