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ΤαξινόμησηΔημοτικότηταΑ–ΩΩ–ΑΝεότερες
psychometrics

2PL IRT

The two-parameter logistic item response model, formalised by Frederic Lord (1980), describes the probability that a respondent answers a binary test item correctly as a smooth S-shaped function of the respondent's latent ability. By estimating a separate discrimination parameter for each item alongside a difficulty pa

2 πηγές1980
psychometrics

3PL IRT

The three-parameter logistic (3PL) model, introduced by Allan Birnbaum in 1968, is an item response theory model that describes the probability of a correct response to a binary test item as a function of three item-level parameters — difficulty, discrimination, and a lower asymptote representing guessing — and one per

2 πηγές1968
educational psychology

Academic Burnout Scale

The Academic Burnout Scale measures three dimensions of student burnout: emotional exhaustion, cynicism toward studies, and reduced academic efficacy. Developed by Schaufeli and colleagues in 2002, it adapts the Maslach Burnout Inventory framework to the academic context, providing researchers and educators with a vali

2 πηγές2002
educational psychology

Academic Help-Seeking Scale

The Academic Help-Seeking Scale measures students' inclination to seek academic help, their preferred sources of assistance (instructors, peers, tutors), and barriers that inhibit help-seeking (fear of judgment, embarrassment, preference for independence). Developed by Karabenick and colleagues in the 1990s, the AHSS r

2 πηγές1990
educational psychology

Academic Integrity Scale

The Academic Integrity Scale measures students' attitudes, values, and likelihood of engaging in academic dishonesty including cheating, plagiarism, and unauthorized collaboration. Multiple validated versions exist, each assessing different facets of academic integrity such as personal integrity commitment, perceived c

2 πηγές2000
educational psychology

Academic Motivation Scale

The Academic Motivation Scale (AMS) is a 28-item self-report instrument developed by Vallerand et al. (1992) to assess the quality of students' academic motivation. It distinguishes between intrinsic motivation (motivation for knowledge, accomplishment, and stimulation), extrinsic motivation (external regulation, intro

2 πηγές1992
educational psychology

Academic Resilience Scale

The Academic Resilience Scale measures the capacity of students to withstand and recover from academic adversity, including setbacks, failures, and difficult transitions. Developed by Cassidy in 2016, the ARS-30 conceptualizes resilience as a dynamic, multidimensional process involving perseverance, adaptive help-seeki

2 πηγές2016
educational psychology

Academic Self-Efficacy Scale

The Academic Self-Efficacy Scale (ASES) measures students' beliefs about their capability to succeed in academic tasks. Grounded in Bandura's social cognitive theory, the instrument assesses perceived competence in diverse academic domains—understanding lectures, completing assignments, performing on exams, and engagin

2 πηγές1977
psychometrics

Anchor-Based Minimal Important Difference

The anchor-based method for establishing Minimal Clinically Important Difference (MCID) is a technique for determining the smallest change in a patient-reported outcome (PRO) that patients or clinicians perceive as meaningful or important. Pioneered by Guyatt, Jaeschke, and Singer in 1989, this approach anchors changes

3 πηγές1989
psychometrics

Bifactor Model

The bifactor measurement model specifies that every indicator loads simultaneously on a single general factor and on one of several specific (group) factors. Formally introduced by Holzinger and Swineford in 1937 and brought into mainstream psychometrics by Reise (2012), it is now the standard tool for evaluating wheth

2 πηγές1937
psychometrics

Case-Cohort Design

Case-cohort design is an epidemiological study design developed by Prentice (1986) that efficiently combines features of case-control and cohort studies. Researchers enroll an entire cohort, follow it for outcomes, then measure exposures only on cases and a random subcohort, reducing measurement costs while maintaining

3 πηγές1986
psychometrics

CAT Generalizability Theory

Generalizability theory (G-theory) applied to computerized adaptive testing (CAT) evaluates the dependability of adaptive test scores by decomposing score variance across measurement facets such as persons, items, and occasions. Unlike classical test theory, G-theory quantifies multiple simultaneous sources of measurem

2 πηγές1972
psychometrics

CAT McDonald's Omega

McDonald's omega adapted for computerized adaptive testing (CAT) quantifies the reliability of ability or trait estimates when different examinees answer different subsets of items. Unlike Cronbach's alpha, omega is grounded in a factor model, making it suitable for the heterogeneous item pools and variable test length

2 πηγές1999
psychometrics

CAT Scale Development

Computerized adaptive test (CAT) scale development is the process of constructing, calibrating, and validating a large item bank such that the assessment algorithm can select items tailored to each examinee's estimated ability or trait level in real time. The result is a measurement instrument that achieves high precis

2 πηγές1970
psychometrics

CAT-DIF

CAT-DIF identifies items in a computerized adaptive test that behave differently across demographic or group subpopulations after controlling for overall ability. Because adaptive algorithms select items non-randomly based on each examinee's estimated proficiency, standard DIF detection methods require adjustment befor

2 πηγές1990
educational psychology

Classroom Environment Scale

The Classroom Environment Scale is a comprehensive instrument measuring the social, emotional, and organizational climate of educational settings. Developed by Moos and Trickett in 1974, the CES assesses students' or teachers' perceptions of classroom relationships, instructional climate, and classroom management. By p

2 πηγές1974
psychometrics

Cognitive Diagnosis Model

Cognitive Diagnosis Models (CDMs) are a family of latent variable models designed to classify examinees according to their mastery of a set of discrete cognitive attributes or skills. The Generalized DINA (G-DINA) framework, introduced by Jimmy de la Torre in 2011, provides a unifying structure that encompasses many sp

1 πηγή2011
psychometrics

Cognitive Diagnostic Computerized Adaptive Testing

Cognitive Diagnostic Computerized Adaptive Testing (CD-CAT) combines computerized adaptive testing (CAT) with cognitive diagnostic models (CDMs) to efficiently assess students' specific skill profiles. Rather than producing a single overall ability score, CD-CAT adaptively selects items to quickly identify which skills

3 πηγές2007
psychometrics

Computerized adaptive test construct validity

Construct validity in computerized adaptive testing evaluates whether the latent trait estimates produced by a CAT instrument genuinely measure the intended psychological or educational construct. Because adaptive algorithms select items individually for each examinee, the validity evidence gathered must account for th

2 πηγές1989
psychometrics

Computerized Adaptive Test Content Validity

Content validity in computerized adaptive testing (CAT) ensures that an adaptively administered assessment adequately samples the intended content domain despite delivering only a subset of items to each examinee. It integrates classical content validity methods with CAT-specific item bank design and content balancing

2 πηγές1975
psychometrics

Computerized Adaptive Test Convergent Validity

Convergent validity assessment for computerized adaptive tests (CATs) examines whether the ability or trait estimates produced by an adaptive algorithm correlate substantially with scores from other measures of the same construct. Because each examinee receives a different subset of items in a CAT, demonstrating that t

2 πηγές1989
psychometrics

Computerized adaptive test discriminant validity

Discriminant validity in computerized adaptive testing (CAT) is the evaluation process confirming that a CAT-administered scale measures its intended construct distinctly from related but conceptually different constructs. Despite the adaptive item-selection mechanism varying each respondent's item set, evidence must b

2 πηγές1959
psychometrics

Computerized adaptive test item response theory

Computerized adaptive testing based on item response theory is a sequential measurement procedure in which a computer algorithm selects successive test items tailored to each examinee's estimated ability level. Drawing on IRT to model item characteristics and ability estimation, CAT delivers precise scores with far few

2 πηγές1970
psychometrics

Computerized adaptive test measurement invariance

Computerized adaptive test measurement invariance evaluates whether a CAT instrument measures the same latent construct with the same psychometric properties across different groups (e.g., gender, language, clinical vs. community) or time points. It combines IRT-based adaptive test frameworks with measurement equivalen

2 πηγές1990
psychometrics

Computerized adaptive test Rasch model

Computerized adaptive testing with the Rasch model selects items in real time based on each examinee's evolving ability estimate, so that every person receives a test precisely calibrated to their proficiency level. The result is a shorter, more efficient measurement instrument that loses none of the precision of a ful

2 πηγές1960
psychometrics

Computerized adaptive test reliability analysis

CAT reliability analysis quantifies measurement precision in computerized adaptive tests where each examinee receives a unique, individually tailored subset of items. Rather than a single classical coefficient, it uses item response theory to express precision as conditional standard error of measurement at each abilit

2 πηγές1970
psychometrics

Construct Validity

Construct validity is the degree to which a test or scale actually measures the theoretical construct it is intended to measure. Introduced by Cronbach and Meehl in 1955, it is the central validity concern in psychological and educational measurement, evaluated by accumulating multiple lines of empirical and logical ev

2 πηγές1955
psychometrics

Content Validity

Content validity is evidence that a measurement instrument adequately samples the full domain of the construct it is intended to measure. It is established through systematic expert review and quantified with indices such as Lawshe's Content Validity Ratio (CVR) and Lynn's Content Validity Index (CVI), making it the fo

2 πηγές1975
psychometrics

Content Validity Ratio

The Content Validity Ratio (CVR) is a quantitative method developed by Charles Lawshe in 1975 for evaluating the extent to which items in a measurement instrument are relevant and representative of a target construct. The method aggregates expert panel judgments into a single validity coefficient for each item, enablin

3 πηγές1975
psychometrics

Convergent Validity

Convergent validity is the degree to which multiple indicators that are theoretically expected to measure the same construct actually correlate with one another. It is one of the two complementary forms of construct validity identified by Campbell and Fiske (1959) and is now routinely assessed via factor loadings and t

2 πηγές1959
educational psychology

Course Experience Questionnaire

The Course Experience Questionnaire (CEQ) is an institutional assessment tool measuring students' perceptions of their learning environment and educational experience in a course. Developed by Wilson, Lizzio, and Ramsden (1997), it assesses dimensions including good teaching, clear goals, appropriate workload, appropri

2 πηγές1997
psychometrics

Differential Item Functioning

Differential item functioning identifies test or survey items that behave differently for examinees from different groups — such as gender, ethnicity, or language background — after controlling for the underlying ability or trait being measured. DIF analysis is essential for fairness evaluation in educational testing a

2 πηγές1970
psychometrics

DINA Model

The DINA Model (Deterministic Inputs, Noisy Outputs) is a cognitive diagnostic model developed by Junker and Sijtsma (2001) that classifies examinees into latent skill classes based on their item response patterns. DINA assumes a deterministic relationship between skill mastery and correct responses, with probabilistic

3 πηγές2001
psychometrics

DINO Model

The DINO Model (Deterministic Inputs, Noisy Outputs—Disjunctive) is a cognitive diagnostic model that relaxes DINA's conjunctive (AND) skill requirement logic. DINO assumes an examinee only needs to master one of multiple possible skill pathways to answer an item correctly, making it suitable for scenarios where skills

3 πηγές2006
psychometrics

Discriminant Validity

Discriminant validity is evidence that a latent construct is empirically distinct from other constructs it should differ from. Originating in Campbell and Fiske's multitrait-multimethod framework (1959), it is a core component of construct validity and a mandatory check in scale development and structural equation mode

2 πηγές1959
psychometrics

Floor and Ceiling Effect

Floor and ceiling effects are psychometric phenomena in which a disproportionately large proportion of respondents achieve the lowest (floor) or highest (ceiling) possible score on a measurement scale. These effects compromise scale reliability and responsiveness, limiting the instrument's ability to distinguish among

3 πηγές2000
psychometrics

Fuzzy-Set Qualitative Comparative Analysis

Fuzzy-Set Qualitative Comparative Analysis (fsQCA) is a set-theoretic method developed by Charles Ragin in the early 2000s that combines the configurational logic of qualitative case studies with the mathematical rigor of fuzzy sets. It bridges qualitative and quantitative research by allowing researchers to examine ca

3 πηγές2000
psychometrics

G-Theory

Generalizability Theory, developed by Lee J. Cronbach and colleagues in the 1960s and formalised by Brennan (2001), is an ANOVA-based framework that extends Classical Test Theory by decomposing observed score variance into multiple, separately identified sources of measurement error — such as raters, tasks, occasions,

2 πηγές1963
psychometrics

Generalizability Theory

Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell rese

2 πηγές1963
psychometrics

Guttman Scale

Guttman scaling is a methodology for constructing unidimensional scales with a cumulative property, developed by Louis Guttman in 1944. The method assumes that items form a perfect or near-perfect hierarchy: if a respondent endorses a harder item, they must endorse all easier items below it. This creates a reproducible

3 πηγές1944
psychometrics

Item Analysis

Item analysis is the foundational psychometric procedure for evaluating the quality of individual test or scale items within the Classical Test Theory (CTT) framework, as systematised by Allen and Yen (1979) and Crocker and Algina (1986). It produces an item difficulty index, an item discrimination index, and a distrac

2 πηγές1979
psychometrics

Item Response Theory

Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale

2 πηγές1952
psychometrics

Likert Scale Construction

Likert scale construction is a systematic methodology for developing attitude measurement instruments using summated rating scales. Introduced by Rensis Likert in 1932, it enables researchers to quantify latent constructs such as attitudes, beliefs, and psychological states by aggregating responses across multiple item

3 πηγές1932
psychometrics

Longitudinal Construct Validity

Longitudinal construct validity evaluates whether a psychological scale measures the same latent construct in the same way across multiple time points. It is tested by progressively constraining a confirmatory factor model across waves and comparing model fit, ensuring that observed change scores reflect genuine change

2 πηγές1993
psychometrics

Longitudinal content validity

Longitudinal content validity evaluates whether the items of a measure adequately and consistently represent the intended content domain not only at a single point in time but across repeated administrations. It ensures that the conceptual coverage of a scale remains appropriate and stable as measurement occasions accu

2 πηγές1995
psychometrics

Longitudinal convergent validity

Longitudinal convergent validity evaluates whether a scale's indicators correlate with theoretically related constructs not just at a single time point but consistently across repeated measurement occasions. It extends standard convergent validity testing into longitudinal designs to ensure that the scale measures the

2 πηγές1997
psychometrics

Longitudinal DIF

Longitudinal differential item functioning detects whether individual test or scale items behave differently across measurement occasions for the same respondents. It extends standard DIF methodology to repeated-measures designs, ensuring that observed change scores genuinely reflect construct change rather than shifts

2 πηγές1980
psychometrics

Longitudinal Discriminant Validity

Longitudinal discriminant validity tests whether a psychological construct measured at two or more time points is empirically distinct across occasions — ensuring that the same construct does not collapse into a single undifferentiated mass over time. It is a prerequisite for meaningful change modeling in panel and lon

2 πηγές1993
psychometrics

Longitudinal Generalizability Theory

Longitudinal generalizability theory extends classical G-theory to repeated-measures and longitudinal designs, decomposing score variance across persons, measurement occasions, raters, and items simultaneously. It quantifies how reliably scores can be generalized across time points, evaluators, and conditions — informa

2 πηγές1990
psychometrics

Longitudinal IRT

Longitudinal IRT extends classical item response theory to data collected at multiple time points, allowing researchers to model both the initial latent trait level and its change over time. It is used in educational assessment, clinical trials, and panel studies where the same items or item banks are administered repe

2 πηγές1991
psychometrics

Longitudinal McDonald's omega

Longitudinal McDonald's omega estimates scale reliability separately at each measurement occasion in a panel or repeated-measures study. By fitting a confirmatory factor model at each wave, it tracks how consistently a set of items measures its target construct over time, detecting erosion or improvement in measurement

2 πηγές1999
psychometrics

Longitudinal Measurement Invariance

Longitudinal measurement invariance testing determines whether a psychological scale measures the same construct in the same way across two or more time points. It is a prerequisite for interpreting mean-level change scores in panel and repeated-measures studies, ensuring that observed change reflects true change in th

2 πηγές1993
psychometrics

Longitudinal Nomological Validity

Longitudinal nomological validity evaluates whether a construct's theoretically predicted relationships with other constructs hold consistently across multiple measurement occasions. It extends the nomological network framework of Cronbach and Meehl (1955) to longitudinal designs, testing whether a scale behaves as the

2 πηγές1955
psychometrics

Longitudinal Reliability Analysis

Longitudinal reliability analysis evaluates the consistency and stability of measurement instruments across two or more time points. It extends classical reliability concepts — internal consistency, test-retest stability, and measurement precision — to repeated-measures designs, ensuring that observed score changes ref

2 πηγές1951
psychometrics

Longitudinal scale development

Longitudinal scale development is the systematic process of constructing and validating a measurement instrument using data collected at multiple time points. It extends classical scale development by additionally testing whether the scale measures the same construct in the same metric across occasions, enabling valid

2 πηγές1990
psychometrics

Longitudinal Test-Retest Reliability

Longitudinal test-retest reliability quantifies how consistently a scale or measure performs across two or more time points in a longitudinal study. It extends the classic test-retest paradigm by accounting for planned, often substantive, time lags between waves — making it essential for validating instruments used in

2 πηγές1904
educational psychology

Mathematics Anxiety Rating Scale

The Mathematics Anxiety Rating Scale (MARS) is a self-report instrument measuring the degree of anxiety students experience in mathematical situations. Developed by Richardson and Suinn (1972) and revised by Plake and Parker (1995), it assesses emotional and physiological responses to math learning and performance. Mat

2 πηγές1972
psychometrics

McDonald's Omega

McDonald's hierarchical omega (ωh) is a coefficient derived from a bifactor confirmatory factor model that quantifies what proportion of total-score variance is attributable to a single general factor rather than to group-specific factors or item-level error. Introduced by Roderick P. McDonald (1999) and elaborated for

2 πηγές1999
psychometrics

McDonald's Omega

McDonald's omega is a factor-analysis-based reliability coefficient introduced by Roderick P. McDonald (1999) that quantifies the internal consistency of a composite score without requiring the restrictive assumption that all items contribute equally to the latent factor. It yields two complementary indices: ω_total, w

2 πηγές1999
psychometrics

MCP Penalized Regression

MCP (Minimax Concave Penalty) is a variable selection method developed by Zhang (2010) that uses a concave penalty function for automated feature selection. Like SCAD, MCP addresses bias in lasso by avoiding shrinkage of large coefficients, but uses a different penalty shape that is computationally simpler than SCAD.

3 πηγές2010
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