ScholarGate
Découvrir
BibliothèqueMa bibliothèqueBureauVérification préalableReview StudioAssistant
Espace de travail
Comparer
Constituez votre bibliothèque

Enregistrez des méthodes, organisez des collections et emportez-les à votre bureau.

Créer un compte
Bibliothèque / Parcourir
Se connecter
La bibliothèque

Explorez la science par méthode, domaine et preuves.

Un catalogue unique des méthodes de recherche — découvrez comment chacune fonctionne, quand l'utiliser et ce qu'elle ne peut pas faire.

6,378 méthodes11 domaines7 familles de méthodes40 langues
Atlas de la scienceCartographiez la structure de la science avant de l'utiliser.Domaines · méthodes · parcours de preuvesExplorer la carte
DomaineHealth & Medicine716Psychology570Business & Finance410Engineering330Life Sciences263Education261Research Practice248Natural Sciences
ScholarGate

Une bibliothèque de référence centrée sur le contenu, dédiée aux méthodes de recherche — ce qu'est chaque méthode, comment elle fonctionne et d'où elle vient.

Données ouvertes (CC-BY)

Découvrir

  • Bibliothèque
  • Rechercher des méthodes…
  • Parcourir par domaine
  • Domaines
  • Cheminement
  • Comparer
  • Quelle méthode ?

Référence

  • Disciplines
  • Atlas
  • Glossaire
  • Méthodologie
  • Philosophie

Espace de travail

  • Ma bibliothèque
  • Bureau
  • Chat

Entreprise

  • À propos
  • Tarifs
  • Contact
  • Proposer une méthode

Les entrées sont compilées à partir de sources publiées à titre de référence. Il vous appartient de vérifier l'exactitude et l'adéquation de toute information à votre propre usage.

© 2026 ScholarGate · Bibliothèque de référence des méthodes de recherche
  • Confidentialité
236
Social Sciences185
Environment & Sustainability160
Law30
MéthodeStatistique1,836IA & apprentissage automatique1,661Sciences de la décision932Méthodes de recherche1,354Mesure1,745Causalité & preuves532Pratique de la recherche118
221 méthodes en EducationEffacer
Des méthodes réelles correspondant à votre filtre.
TrierPopularitéA–ZZ–ALes plus récentes
psychometrics

Multilevel Content Validity

Multilevel content validity extends the classical content validity framework to settings where items, raters, or respondents are nested within hierarchical structures — such as students within schools, patients within clinics, or items rated by panels from distinct cultural or professional groups. It ensures that scale

2 sources1975
psychometrics

Multilevel Convergent Validity

Multilevel convergent validity evaluates whether items or scales intended to measure the same construct show coherent, strong associations at each level of a nested data structure — within individuals, within groups, and between groups. It extends classical convergent validity from single-level measurement models into

2 sources2005
psychometrics

Multilevel Differential Item Functioning

Multilevel DIF analysis detects whether individual test or survey items function differently across groups when respondents are clustered within higher-level units — such as students nested in schools, employees in organizations, or patients in clinics. By accounting for hierarchical data structure, it separates genuin

2 sources2001
psychometrics

Multilevel Discriminant Validity

Multilevel discriminant validity evaluates whether theoretically distinct constructs are empirically separable when data are nested within higher-level units such as teams, schools, or organizations. It extends single-level discriminant validity checks into a multilevel confirmatory factor analysis framework, verifying

2 sources2005
psychometrics

Multilevel EFA

Multilevel exploratory factor analysis uncovers latent factor structures simultaneously at two or more levels of a data hierarchy — for example, both within individuals and between groups — without imposing a fixed structure in advance. It is essential whenever survey or test items are collected from respondents nested

2 sources1994
psychometrics

Multilevel Generalizability Theory

Multilevel generalizability theory extends classical G-theory to measurement designs where observations are nested within higher-level units — for example, items nested within raters, or students nested within classrooms. It decomposes score variance into components attributable to persons, facets, and their interactio

2 sources1990
psychometrics

Multilevel McDonald's omega

Multilevel McDonald's omega estimates reliability at two distinct levels — within groups and between groups — for scales administered to individuals nested in clusters such as classrooms, teams, or organizations. It accounts for the non-independence induced by grouping and avoids the bias that single-level omega produc

2 sources1999
psychometrics

Multilevel Measurement Invariance

Multilevel measurement invariance testing evaluates whether a latent construct is measured equivalently both within clusters (e.g., individuals within teams) and between clusters (e.g., team-level aggregates). It extends standard measurement invariance procedures to nested data structures commonly encountered in organi

2 sources2000
psychometrics

Multilevel nomological validity

Multilevel nomological validity evaluates whether a psychological construct and its network of theoretical relationships hold consistently across multiple levels of analysis — such as individual, team, and organization. It extends classical construct validation to nested data structures, ensuring that a measure means t

2 sources2005
psychometrics

Multilevel Rasch Model

The multilevel Rasch model extends the standard Rasch model to data with a nested structure — for example, students within classrooms within schools — by embedding person ability parameters inside a hierarchical linear model. It yields item difficulty estimates on a logit scale while simultaneously partitioning person-

2 sources1997
psychometrics

Multilevel Reliability Analysis

Multilevel reliability analysis estimates the internal consistency of scale scores separately at the within-group (individual) and between-group (cluster) levels. It corrects the bias that arises when ordinary alpha or omega is applied to hierarchically nested data, such as employees within organizations or students wi

2 sources2014
psychometrics

Multilevel Scale Development

Multilevel scale development constructs and validates measurement instruments for data collected from individuals nested within higher-level units such as classrooms, organizations, or clinics. It partitions item variance into within-group and between-group components, ensuring that reliability and factor structure are

2 sources1990
psychometrics

Multilevel Test-Retest Reliability

Multilevel test-retest reliability estimates how consistently a measurement instrument produces the same scores across repeated administrations when observations are nested within higher-level units — such as patients within clinics or students within classrooms. It partitions total score variance across levels using i

2 sources1979
psychometrics

Multiple Factor Analysis

Multiple Factor Analysis (MFA) is a dimension reduction technique developed by Escofier and Pagès (1985) for analyzing multiple groups of variables measured on the same observations. MFA balances the influence of each variable group to provide a unified view of how observations relate across multiple perspectives.

3 sources1985
health education

NCCS

The NCCS is a multidimensional self-assessment and clinician-rated instrument measuring nursing students' perceived and observed clinical competence across technical, interpersonal, and cognitive domains. Developed by Walt and van der Walt in 2009, the scale evaluates students' mastery of fundamental nursing skills, cr

2 sources2009
psychometrics

Necessary Condition Analysis

Necessary Condition Analysis (NCA) is a set-theoretic method developed by Dul (2016) that identifies conditions necessary (but not necessarily sufficient) for an outcome to occur. Unlike regression, which estimates average effects, NCA identifies absolute thresholds: conditions that must be present at a certain level f

3 sources2016
psychometrics

Nomological Validity

Nomological validity evaluates whether a construct behaves as theory predicts within a broader network of related constructs. It is not a single statistical test but an accumulation of evidence that the measure fits coherently into a web of theoretically grounded relationships — demonstrating that what is measured is w

2 sources1955
psychometrics

Ordinal CFA

Ordinal confirmatory factor analysis (Ordinal CFA) tests a pre-specified factor structure when the observed indicators are ordinal — typically Likert-type survey items. By using polychoric correlations and robust estimators such as WLSMV, it avoids the bias that arises from treating categorical responses as continuous.

2 sources1984
psychometrics

Ordinal Content Validity

Ordinal content validity replaces the traditional binary (yes/no) expert relevance judgment with a graded, Likert-type rating scale, allowing richer expert opinion to be captured when evaluating whether scale items adequately represent the intended construct domain.

2 sources2003
psychometrics

Ordinal Convergent Validity

Ordinal convergent validity assesses the degree to which indicators of the same latent construct correlate strongly with each other when those indicators are measured on ordinal (e.g., Likert-type) scales. It adapts standard convergent validity procedures — factor loadings, average variance extracted, and HTMT ratios —

2 sources1959
psychometrics

Ordinal Cronbach's Alpha

Ordinal Cronbach's alpha is a reliability coefficient computed from polychoric or polyserial correlations rather than Pearson correlations, making it appropriate for Likert-type and other ordinal item response data. It corrects the systematic downward bias that standard Cronbach's alpha produces when items are treated

2 sources2007
psychometrics

Ordinal Differential Item Functioning

Ordinal differential item functioning analysis detects whether an ordered-category item (such as a Likert-scale question) functions differently across demographic or cultural groups after controlling for the latent trait being measured. It extends classical binary DIF methods to polytomous response formats common in ps

2 sources1999
psychometrics

Ordinal Discriminant Validity

Ordinal discriminant validity assesses whether a latent construct measured by ordinal (Likert-type) items is empirically distinct from other constructs in the same instrument. It applies polychoric correlations and ordinal-appropriate factor loadings to standard discriminant validity criteria such as the Fornell-Larcke

2 sources1959
psychometrics

Ordinal EFA

Ordinal exploratory factor analysis discovers latent factors underlying a set of ordinal items — typically Likert scales — by computing polychoric correlations among the items and then applying a weighted least squares estimator. It avoids the distortions that arise when continuous EFA methods are naively applied to or

2 sources1978
psychometrics

Ordinal Generalizability Theory

Ordinal generalizability theory extends classical G-theory to the analysis of reliability and measurement error when item responses are ordered categorical (e.g., Likert-type) rather than continuous. It partitions score variance into components attributable to persons, facets, and their interactions, while accounting f

2 sources1963
psychometrics

Ordinal IRT

Ordinal item response theory (ordinal IRT) comprises a family of probabilistic models — most notably the Graded Response Model and the Partial Credit Model — that relate a respondent's standing on a latent trait to the probability of choosing each ordered response category on a polytomous item. It extends classical IRT

2 sources1969
psychometrics

Ordinal Item Analysis

Ordinal item analysis evaluates each individual item in a rating-scale or Likert-type instrument using descriptive and correlational statistics suited to ordered categorical response formats. It guides item selection and refinement by flagging items with problematic difficulty, poor discrimination, or low corrected ite

2 sources1950
psychometrics

Ordinal McDonald's omega

Ordinal McDonald's omega is a reliability coefficient designed for Likert-type and other ordinal rating scales. Unlike Cronbach's alpha, it bases its calculation on polychoric correlations among items — capturing the true latent relationships between ordinal responses — and uses factor-analytic loadings to estimate how

2 sources2007
psychometrics

Ordinal Measurement Invariance

Ordinal measurement invariance testing evaluates whether a multi-group confirmatory factor model holds equivalent measurement properties across groups when scale items are ordinal — such as Likert-type response scales. It uses polychoric correlations and categorical estimators (WLSMV/DWLS) rather than Pearson-based met

2 sources1984
psychometrics

Ordinal Nomological Validity

Ordinal nomological validity examines whether a construct measured with ordinal items (e.g., Likert-type scales) behaves in theoretically predicted ways within a nomological network — a web of expected relationships with other constructs and criteria — using methods suited to ordinal data rather than assuming continuou

2 sources1955
psychometrics

Ordinal Rasch Model

The ordinal Rasch model extends the dichotomous Rasch framework to items with ordered response categories such as Likert-type scales. It places both persons and items on a shared interval-level metric, enabling principled measurement from ordinal data while checking whether items function consistently across all respon

2 sources1978
psychometrics

Ordinal Reliability Analysis

Ordinal reliability analysis estimates the internal consistency of scales whose items are measured on ordered-category (Likert-type) response formats. By basing computations on polychoric correlations rather than Pearson correlations, it corrects for the attenuation that standard Cronbach's alpha produces when response

2 sources2007
psychometrics

Ordinal Scale Development

Ordinal scale development is the systematic construction and validation of multi-item measurement instruments whose response options form an ordered but not necessarily equal-interval sequence — most commonly Likert-type formats (e.g., 1 = Strongly Disagree to 5 = Strongly Agree). It applies psychometric techniques tha

2 sources1932
psychometrics

Ordinal Test-Retest Reliability

Ordinal test-retest reliability quantifies how consistently an ordinal measurement instrument — such as a Likert-scale questionnaire or a rating tool — ranks or scores the same participants across two separate administrations separated by a stable interval, using correlation and agreement statistics suited to ordered c

2 sources1904
psychometrics

Partial Least Squares Structural Equation Modeling

PLS-SEM is a variance-based approach to structural equation modeling developed by Herman Wold (1985) that estimates latent variable models by maximizing the variance explained in dependent variables. Unlike covariance-based SEM, PLS-SEM is particularly useful for exploratory research, small to medium samples, complex m

3 sources1985
psychometrics

PCM / GPCM

The Partial Credit Model is an extension of the Rasch measurement framework designed for ordered polytomous items — items whose responses fall into more than two ordered categories, such as partial-credit tasks in performance assessment or open-ended scoring rubrics. Proposed by Geoff Masters in 1982 and later generali

2 sources1982
educational psychology

Peer Learning Scale

The Peer Learning Scale measures the extent and quality of collaborative learning experiences among students, capturing the frequency of peer interaction, perceived support from peers, quality of peer feedback, and learning gains from collaboration. Grounded in social-constructivist theory and decades of research on co

2 sources2000
health education

PIS

The PIS is a self-report questionnaire measuring healthcare students' sense of professional identity, belonging, and commitment to their chosen discipline. Developed by Adams and colleagues in 2006, the PIS assesses the degree to which students have internalized professional roles, values, behaviors, and career commitm

2 sources2006
psychometrics

Polytomous Confirmatory Factor Analysis

Polytomous confirmatory factor analysis (CFA) tests a pre-specified factor structure when items have three or more ordered response categories (e.g., Likert scales). By working with polychoric correlations and robust estimators such as WLSMV, it avoids the distortions that arise when ordered categorical data are treate

2 sources1984
psychometrics

Polytomous Construct Validity

Polytomous construct validity refers to the evaluation of whether a scale composed of ordered, multi-category items (e.g., Likert or rating-scale items) genuinely measures the intended latent construct. It extends classical validity frameworks to polytomous measurement models — such as the Graded Response Model or Gene

2 sources1992
psychometrics

Polytomous DIF

Polytomous differential item functioning detects whether a test or survey item with more than two ordered response categories (e.g., Likert-type scales, partial-credit items) functions differently across groups such as gender, ethnicity, or language background, after controlling for the latent trait being measured. It

2 sources1990
psychometrics

Polytomous EFA

Polytomous exploratory factor analysis extends standard EFA to ordered categorical (Likert-type) response data by replacing the Pearson correlation matrix with a polychoric correlation matrix. It recovers the latent continuous variable that each polytomous item is assumed to reflect, yielding more accurate factor loadi

2 sources1978
psychometrics

Polytomous item analysis

Polytomous item analysis examines the psychometric behavior of items that have more than two ordered response categories — such as Likert-type scales or partial-credit tasks. It evaluates each item's difficulty thresholds, discriminating power, and category functioning to determine whether the full response scale is be

2 sources1969
psychometrics

Polytomous McDonald's omega

Polytomous McDonald's omega estimates the internal consistency reliability of a scale composed of ordinal (polytomous) items — such as Likert-type responses — by computing omega from a factor model fitted to the polychoric correlation matrix rather than the Pearson correlation matrix, yielding estimates that are unbias

2 sources1999
psychometrics

Polytomous Measurement Invariance

Polytomous measurement invariance testing evaluates whether a scale with ordered categorical (polytomous) response options — such as Likert-type items — measures the same latent construct in the same way across two or more groups. It extends classical multi-group CFA invariance testing to properly account for the ordin

2 sources2000
psychometrics

Polytomous Rasch Model

The Polytomous Rasch Model extends the dichotomous Rasch framework to ordered response scales with three or more categories, such as Likert items or partial-credit tasks. It estimates person ability and item difficulty on the same interval-level logit scale, and it tests whether the response categories function as inte

2 sources1978
psychometrics

Polytomous Reliability Analysis

Polytomous reliability analysis estimates the internal consistency or precision of measurement for scales composed of items with more than two ordered response categories, such as Likert-type, rating, or partial-credit items. It corrects a well-known underestimation bias in conventional Cronbach's alpha by working with

2 sources2007
psychometrics

Polytomous scale development

Polytomous scale development is the systematic construction and validation of measurement instruments whose items have three or more ordered response categories — such as Likert-type, rating, or partial-credit items. It applies polytomous item response theory models or ordinal factor analysis methods to evaluate item q

2 sources1969
psychometrics

Process Tracing

Process Tracing is a qualitative research method developed by George and Bennett (2005) for studying causal mechanisms and causal chains within individual cases. It involves examining the sequence of events and decision-making processes within a case to infer whether a hypothesized causal mechanism actually operated. P

3 sources2005
educational psychology

Procrastination Assessment Scale for Students

The Procrastination Assessment Scale for Students is a comprehensive instrument measuring the frequency of academic procrastination across multiple task types and identifying the underlying reasons for delay. Developed by Solomon and Rothblum in 1984, the PASS provides educators and researchers with actionable data abo

2 sources1984
health education

PSCS

The PSCS is a self-report instrument measuring healthcare students' and professionals' self-perceived competence in patient safety practices, safety awareness, and safety culture engagement. Developed by Lachman and informed by James Reason's theoretical framework of human error and systems thinking, the PSCS evaluates

2 sources2012
psychometrics

Rasch Model

The Rasch model, introduced by Georg Rasch in 1960, is the simplest member of the Item Response Theory (IRT) family. It assigns a single difficulty parameter to each test item and places both item difficulties and person abilities on the same logit scale, enabling direct, sample-independent comparison of items and pers

2 sources1960
psychometrics

Redundancy Analysis

Redundancy Analysis (RDA) is a multivariate technique developed by van den Wollenberg (1977) that combines multiple regression and principal component analysis. RDA finds linear combinations of predictor variables that best predict variation in response variables, making it ideal for understanding how sets of predictor

3 sources1977
health education

RIPLS

The RIPLS is a 19-item self-report questionnaire designed to measure healthcare students' attitudes and readiness toward interprofessional learning and collaboration. Developed by Parsell and Bligh in 1999, it assesses three core dimensions of interprofessional readiness: teamwork and collaboration, professional identi

1 source1999
psychometrics

Robust Content Validity

Robust content validity assessment applies outlier-resistant statistical methods to the aggregation of expert panel ratings in content validation studies. By detecting and down-weighting idiosyncratic or extreme rater judgements, it yields Content Validity Ratio (CVR) and Content Validity Index (CVI) estimates that ref

2 sources1975
psychometrics

Robust Cronbach's Alpha

Robust Cronbach's alpha adapts the classical internal consistency coefficient to data that violate the assumption of multivariate normality or contain influential outliers. By replacing the conventional sample covariance matrix with a robust counterpart, it yields a reliability estimate that is resistant to distortion

2 sources2002
psychometrics

Robust Differential Item Functioning

Robust differential item functioning analysis detects items that behave differently across demographic groups after matching respondents on the underlying trait, while protecting the procedure against distortion by outliers, model misfit, or contaminated anchor items. It is applied in educational testing, clinical asse

2 sources1990
psychometrics

Robust Discriminant Validity

Robust discriminant validity assessment determines whether distinct latent constructs in a measurement model are sufficiently different from one another. Unlike traditional AVE-based approaches, robust methods such as the Heterotrait-Monotrait (HTMT) ratio use the pattern of inter-indicator correlations to provide a mo

2 sources1959
psychometrics

Robust Exploratory Factor Analysis

Robust exploratory factor analysis discovers the latent factor structure of a set of items using estimation methods that are resistant to outliers and violations of multivariate normality. It applies the same measurement model as standard EFA but replaces classical covariance estimation with robust counterparts — such

2 sources2000
psychometrics

Robust Item Analysis

Robust item analysis applies outlier-resistant statistical methods to the evaluation of individual test or scale items. Instead of classical means and Pearson correlations — both sensitive to extreme scores — it uses trimmed means, Winsorized correlations, or M-estimators to obtain item difficulty and item-total discri

2 sources1980
← 23 / 44 →
  • Cookies
  • Conditions
  • Supprimer le compte