Statistics — Page 8
Explore statistical methods, their assumptions, interpretation and limitations.
Research field
Method family
Rescorla-Wagner Model
The Rescorla-Wagner Model is a quantitative theory of associative learning that predicts how organisms learn associations between stimuli (e.g., tone and shock in fear conditioning). The model proposes that learning is driven by prediction...
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...
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 robus...
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, o...
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-Monotr...
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 E...
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, Winsoriz...
Robust McDonald's Omega
Robust McDonald's omega estimates the internal consistency reliability of a composite scale using factor-analytic loadings obtained through robust estimation methods (such as MLR or DWLS). Unlike standard omega or Cronbach's alpha, it remai...
Robust Measurement Invariance
Robust measurement invariance testing evaluates whether a psychometric instrument measures the same latent construct in the same way across groups when observed data violate multivariate normality. It adapts standard multi-group CFA sequenc...
Robust Nomological Validity
Robust nomological validity evaluates whether a psychological construct relates to theoretically expected variables in the predicted directions, using statistically robust estimation methods that remain trustworthy when distributional assum...
Robust Rasch Model
The robust Rasch model applies the standard one-parameter logistic Rasch framework with estimation procedures designed to limit the influence of outlying item responses, aberrant respondents, or mild model violations, producing stable item...
Robust Test-Retest Reliability
Robust test-retest reliability quantifies how consistently a measure ranks or scores the same individuals across two occasions while protecting the estimate from distortion by outliers and non-normal score distributions. It replaces or supp...
Rule Space Methodology
Rule Space Methodology (RSM) is a diagnostic classification approach developed by Tatsuoka (1983) that uses Item Response Theory and geometric methods to classify examinees into knowledge states based on their response patterns. Unlike clas...
SCAD Penalized Regression
SCAD (Smoothly Clipped Absolute Deviation) is a variable selection and regularization method developed by Fan and Li (2001) that addresses limitations of L1 penalization (lasso). SCAD uses a non-concave penalty that automatically performs v...
SIBTEST
SIBTEST (Simultaneous Item Bias Test) is a non-parametric method for detecting differential item functioning (DIF) and differential test functioning (DTF) developed by Shealy and Stout (1993). Unlike parametric approaches, SIBTEST does not...
Scale development
Scale development is a structured, multi-step process for creating psychometrically sound measurement instruments that capture latent psychological constructs. It encompasses construct definition, item generation, expert review, exploratory...
Self-Monitoring Scale
The Self-Monitoring Scale, introduced by Mark Snyder in 1974, measures the extent to which people observe and control their expressive behavior and self-presentation in response to situational and interpersonal cues. High self-monitors are...
Semantic Differential
The Semantic Differential is an attitude measurement technique that assesses the connotative meaning (emotional and evaluative associations) of concepts through ratings on multiple bipolar adjective scales. Developed by Osgood, Suci, and Ta...
Short Form Measurement Invariance
Short form measurement invariance testing evaluates whether an abbreviated version of a psychological scale measures the same latent construct equivalently across groups or conditions. It applies the hierarchical multigroup confirmatory fac...
Short form Rasch model
The short form Rasch model applies Rasch measurement theory to abbreviated instrument versions. Rather than using all items from a full scale, researchers select a reduced item set and calibrate it under the Rasch model to verify that the s...
Short form construct validity
Short form construct validity is the systematic evaluation of whether an abbreviated version of a psychological scale still measures the same underlying construct as the original full-length instrument. It combines item selection procedures...
Short form content validity
Short-form content validity evaluates whether items retained in an abbreviated scale still adequately represent every substantive facet of the construct measured by the original full-length instrument. It ensures that shortening a scale doe...
Short form differential item functioning
Short-form differential item functioning (DIF) analysis examines whether individual items in an abbreviated scale function equivalently across demographic or subgroup comparisons. When a scale is shortened, retained items must still behave...
Short form generalizability theory
Short form generalizability theory applies the G-theory variance-component framework to abbreviated measurement instruments, using G-studies and D-studies to estimate how many items a short scale must retain to achieve a desired reliability...