Jediný katalog výzkumných metod — zjistěte, jak každá funguje, kdy ji použít a co nedokáže.
Bayesian confirmatory factor analysis tests a pre-specified factor structure using Bayesian inference. Instead of point estimates with p-values, it produces full posterior distributions for loadings, factor correlations, and residual variances, allowing the researcher to incorporate prior knowledge and propagate parame
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
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
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
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
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
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
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
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
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
Bayesian construct validity assessment uses Bayesian confirmatory factor analysis and related Bayesian structural equation models to evaluate whether a scale or test measures the intended latent construct. It yields full posterior distributions for factor loadings, structural coefficients, and model-fit indices rather
Bayesian convergent validity applies Bayesian statistical inference to assess whether different measures of the same construct converge as theory predicts. Rather than a single-point correlation estimate, it yields a full posterior distribution over the convergent correlation, enabling probability statements about the
Bayesian Cronbach's alpha applies Bayesian inference to estimate the classical internal-consistency coefficient, yielding a full posterior distribution over alpha rather than a single point estimate. This allows researchers to quantify uncertainty with credible intervals and incorporate prior knowledge, making reliabil
Bayesian differential item functioning analysis detects whether a test item behaves differently across demographic or cultural groups — such as males vs. females — after accounting for the underlying ability or trait being measured. It applies Bayesian IRT estimation to obtain posterior distributions of item parameters
Bayesian discriminant validity assessment evaluates whether two theoretically distinct latent constructs are empirically separable, using posterior distributions and credible intervals rather than single-point null-hypothesis tests. It is applied within Bayesian confirmatory factor analysis or via the Bayesian heterotr
Bayesian exploratory factor analysis applies a full probabilistic framework to the common factor model. By placing prior distributions over factor loadings and unique variances, it yields posterior distributions rather than point estimates, quantifies uncertainty around every loading, and can treat the number of factor
Bayesian item analysis applies Bayesian inference to estimate item-level statistics — difficulty, discrimination, and distractor effectiveness — by combining observed response data with prior knowledge. It produces full posterior distributions over item parameters rather than single point estimates, providing richer un
Bayesian McDonald's omega applies Bayesian statistical estimation to the omega reliability coefficient, yielding a full posterior distribution over omega rather than a single point estimate. This provides credible intervals and probabilistic uncertainty quantification for the reliability of a composite or scale score,
Bayesian measurement invariance testing evaluates whether a scale's factor loadings and item intercepts are equivalent across groups, using a Bayesian framework that allows parameters to deviate from strict equality by a small, probabilistically specified amount rather than imposing an exact constraint.
Bayesian scale development applies Bayesian statistical inference to the construction and evaluation of psychometric scales. Rather than relying on single point estimates of item and person parameters, it produces full posterior distributions that quantify uncertainty, incorporate prior knowledge, and support principle
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
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
Cronbach's alpha applied to computerized adaptive test (CAT) data estimates internal consistency reliability under the special condition that different examinees receive different subsets of items. Because the classic formula assumes every respondent answers the same items, its direct application to CAT data violates c
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
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
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
Computerized adaptive test (CAT) test-retest reliability quantifies the consistency of ability estimates obtained when the same examinees complete a CAT on two separate occasions. Because adaptive algorithms tailor each examinee's item set individually, traditional reliability frameworks must be adapted to account for
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
Confirmatory factor analysis is a measurement modelling technique that tests whether a hypothesised factor structure — typically derived from theory or an earlier exploratory analysis — fits observed data from a new sample. Developed by Karl Jöreskog in 1969, it became the dominant tool for validating psychological sca
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
The CLES+T is a 34-item self-report questionnaire measuring nursing students' perceptions of their clinical learning environment and the quality of supervision received from their clinical preceptor or teacher. Originally developed by Saarikoski and colleagues in 2007 and expanded in 2008 to include a specific teacher
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
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
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
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
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
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
Computerized adaptive test item analysis evaluates and calibrates items intended for use in adaptive testing environments. Unlike fixed-form analysis, it accounts for the non-random item exposure inherent in adaptive administration, using item response theory to estimate item parameters, information functions, and expo
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
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
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
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
Computerized Adaptive Testing (CAT) is an individualized assessment methodology in which a computer algorithm selects successive test items based on a running estimate of each examinee's latent ability. Grounded in Item Response Theory, CAT dynamically tailors the item sequence so that each question is optimally inform
Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix
Confirmatory Factor Analysis (CFA) is a statistical method for testing whether a hypothesized factorial structure fits empirical data. Developed by Karl G. Jöreskog in 1969, CFA is the standard approach for validating psychometric scales by evaluating whether items load onto theoretically specified latent factors as ex
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
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
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
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
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
The Critical Thinking Dispositions Scale (CTDS), exemplified by the California Critical Thinking Disposition Inventory (CCTDI), measures the extent to which individuals exhibit cognitive dispositions conducive to critical thinking. Developed by Facione (1992), it assesses dimensions including truth-seeking, open-minded
The CTQS is a self-report questionnaire measuring students' perceptions of their clinical educator's (preceptor, clinical instructor, or mentor) teaching quality and effectiveness. Developed by Ohrling, Hallberg, and Gaberson in the early 2000s, the CTQS evaluates dimensions of clinical teaching including role modeling
The DASH is a 20-item observer-rated instrument measuring the quality of debriefing—the structured, facilitated reflection following a healthcare simulation activity. Developed by Rudolph, Simon, and Raemer in 2006 at Massachusetts General Hospital, the DASH evaluates the debriefing facilitator's ability to create a ps
Differential Item Functioning analysis examines whether examinees from different groups — such as gender, ethnicity, or language background — who have the same underlying ability respond differently to a test item. First formalised by Holland and Thayer in 1988 via the Mantel-Haenszel procedure, it is the principal too
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
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
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
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
Exploratory Factor Analysis for Scale Development is the psychometric application of EFA in which an item pool is administered and the resulting response data are analysed to discover the latent factor structure underlying the items. Originating with Spearman's (1904) factor theory and formalised for applied scale cons
Exploratory Structural Equation Modeling (ESEM) is a hybrid approach that combines exploratory factor analysis (EFA) with confirmatory factor analysis (CFA) and path modeling, developed by Asparouhov and Muthén (2009). ESEM relaxes restrictive zero-loading assumptions of traditional CFA, allowing all indicators to load