Statistics — Page 50
Explore statistical methods, their assumptions, interpretation and limitations.
Research field
Method family
Political Cynicism Scale
The Political Cynicism Scale measures the disposition to hold politicians and politics in disrepute, viewing officeholders as dishonest, self-serving, and unresponsive. First operationalized by Agger, Goldstein, and Pearl in 1961, the const...
Political Ideology Scaling
Political ideology scaling estimates actors' positions on one or more latent ideological dimensions from their observed choices, most often legislators' roll-call votes, but also survey responses and donations. The dominant methods are Pool...
Political Survival Analysis
Political survival analysis applies survival and event-history models to the time leaders, governments, and regimes remain in power before failing. Methodologically it rests on the hazard-modeling apparatus codified for social scientists by...
Polynomial Regression
Polynomial regression is a regression method that models non-linear relationships by including squared and higher-degree terms of an explanatory variable, and it is a core tool of response surface analysis. As developed in Montgomery, Peck...
Polynomial Regression with Response Surface Analysis
Polynomial regression with response surface analysis is the methodological gold standard for testing congruence, fit, and agreement hypotheses in organizational behavior, introduced by Jeffrey Edwards and Mark Parry in 1993. It replaces the...
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 WLSM...
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 framewo...
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...
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...
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 matri...
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 extend...
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-...
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...
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 po...
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 i...
Pooled Mean Group (PMG)
The Pooled Mean Group (PMG) estimator, introduced by Pesaran, Shin, and Smith (1999), is a panel data technique designed for dynamic heterogeneous panels where the long-run equilibrium relationship is common across groups but short-run dyna...
Pooled OLS
Pooled OLS applies standard ordinary least squares to panel data by stacking all cross-sectional and time observations into a single dataset and ignoring the panel structure during estimation. It is the most transparent starting point for p...
Population Pharmacokinetics
Population Pharmacokinetics (PopPK) is a nonlinear mixed-effects modeling framework that characterizes how drugs are absorbed, distributed, metabolized, and eliminated across a patient population, estimating both typical population paramete...
Potassium-Argon Dating
Potassium-argon (K-Ar) dating is a radiometric technique that determines the age of volcanic rocks and minerals from the slow radioactive decay of potassium-40 to argon-40. Potassium is abundant in many rock-forming minerals, and a fixed fr...
Power Analysis for ANOVA
Power analysis for ANOVA is a prospective statistical technique that determines the minimum sample size needed to detect a specified group mean difference with a chosen probability. Formalized by Jacob Cohen in his 1988 monograph, it transl...
Power Analysis for Proportions
Power analysis for proportion tests is a prospective sample-size planning method used to determine how many participants are needed to detect a meaningful difference between two (or one) proportions with a specified probability. Formalised...
Power Analysis for Regression
Power analysis for multiple regression is a pre-study procedure, formalised by Jacob Cohen (1988), that calculates the minimum sample size needed to detect a regression effect of a given size with adequate statistical power. It uses the ant...
Power Analysis for t-test
Power analysis for the t-test is a sample size planning procedure that determines how many participants are required to detect a mean difference of a given magnitude with acceptable probability. Formalised by Jacob Cohen in his 1969 and 198...
Power analysis
Power analysis is a planning and evaluation technique that quantifies the probability of detecting a real effect of a given magnitude at a chosen significance level. It links four quantities — sample size, effect size, significance level (a...