Statistics — Page 21
Explore statistical methods, their assumptions, interpretation and limitations.
Research field
Method family
First-Click Testing
First-Click Testing is a rapid, quantitative method for evaluating whether users click on the correct element to start a task on a web page or screen. Users view a screenshot or live page and are asked to click where they would start a spec...
First-Difference Estimator
The First-Difference (FD) estimator is a panel data method that eliminates unobserved, time-invariant individual heterogeneity by subtracting each unit's observation in period t-1 from its observation in period t. By operating on changes ra...
Fisher Panel Unit-Root Test
The Fisher-type (Maddala-Wu) panel unit-root test, introduced in 1999, combines individual-level ADF unit-root p-values using Fisher's chi-squared meta-analytic framework to produce a single panel-level test statistic. Unlike the Levin-Lin-...
Fisher's exact test
Fisher's exact test is a nonparametric exact-probability test of independence for small-sample contingency tables, introduced by R. A. Fisher in 1922. Rather than relying on a large-sample approximation, it computes the exact probability of...
Fitts's Law
Fitts's Law is an empirical model of human rapid aimed movement, predicting that movement time increases logarithmically with the ratio of distance to target size. Formulated by Paul Fitts in 1954, this fundamental law describes how long it...
Fixed Effects Model
The fixed effects (FE) model is the workhorse estimator for panel data when unobserved unit-specific characteristics are suspected to correlate with the regressors. By absorbing each entity's time-invariant heterogeneity into a separate int...
Fixed Effects Panel Model
The fixed effects panel model estimates relationships in panel data (many units observed over time) by exploiting only the within-unit variation, so that unobserved time-invariant heterogeneity is controlled away. It is the central within e...
Fleiss' Kappa
Fleiss' Kappa is a non-parametric statistic for measuring the degree of agreement among three or more raters who classify items into mutually exclusive nominal categories. Introduced by Joseph L. Fleiss in 1971 as a generalization of Cohen'...
Fligner-Killeen Test
The Fligner-Killeen test is a rank-based test that checks whether several independent groups share the same variance (scale). Introduced by Fligner and Killeen in 1976, it does not require the data to be normally distributed, making it a ro...
Flow State Scale-2
The Flow State Scale-2 (FSS-2) is a 36-item self-report instrument developed by Susan Jackson and Robert Eklund (2002) to measure flow — the state of optimal experience and total absorption — as it occurs in a specific physical-activity epi...
Food Insecurity Experience Scale
The Food Insecurity Experience Scale (FIES) is an experience-based metric of food insecurity built on eight yes/no survey questions and calibrated with a Rasch (one-parameter logistic) item response model. Developed by FAO's Voices of the H...
Forensic Likelihood Ratio
The Forensic Likelihood Ratio (LR) is a Bayesian framework for quantifying the weight of forensic evidence relative to two competing propositions — typically the prosecution and defence hypotheses. Formally developed and systematised by Col...
Fourier ADF unit root test
The Fourier ADF unit root test extends the standard Augmented Dickey-Fuller framework by incorporating low-frequency Fourier terms into the deterministic component. This allows the test to approximate smooth, gradual structural breaks in th...
Fourier AR Model
The Fourier AR model extends the standard autoregressive specification by adding trigonometric (sine and cosine) terms to the deterministic component. This allows the model to capture smooth, gradual shifts in the mean or trend of a time se...
Fourier ARCH Model
The Fourier ARCH model extends the classical ARCH framework by incorporating trigonometric (Fourier) terms into the conditional variance equation. This allows the model to capture smooth, gradual shifts in volatility dynamics over time with...
Fourier ARDL Bounds Test
The Fourier ARDL bounds test augments the Pesaran-Shin-Smith cointegration framework with trigonometric (Fourier) terms that capture gradual, smooth structural breaks in the data-generating process. It tests for a long-run level relationshi...
Fourier ARIMA model
The Fourier ARIMA model augments a standard ARIMA specification with trigonometric sine and cosine terms, allowing it to capture smooth, gradual structural change and flexible nonlinear seasonality without specifying the exact timing or num...
Fourier ARMA model
The Fourier ARMA model augments the classical Autoregressive Moving Average framework with low-frequency Fourier (sine and cosine) terms to capture smooth, gradual shifts in the mean or trend of a time series. Unlike dummy-variable approach...
Fourier Arellano-Bond GMM
Fourier Arellano-Bond GMM is a dynamic panel estimator that augments the classic Arellano-Bond first-differenced GMM framework with Fourier trigonometric terms to capture smooth, gradual structural breaks in the time dimension. It handles e...
Fourier DCC-GARCH
The Fourier DCC-GARCH model extends Engle's Dynamic Conditional Correlation GARCH framework by embedding Fourier trigonometric terms in the conditional mean or variance equations. This allows the model to approximate smooth, gradual structu...
Fourier Dynamic Panel Data Model
The Fourier dynamic panel data model extends standard dynamic panel specifications by incorporating low-frequency trigonometric (Fourier) terms to flexibly capture smooth, gradual structural breaks or time-varying patterns in the data, with...
Fourier EGARCH
Fourier EGARCH extends Nelson's (1991) Exponential GARCH model by embedding Fourier trigonometric terms in the conditional variance equation to capture smooth, gradual shifts in the unconditional variance level over time. This allows the mo...
Fourier Engle-Granger cointegration
The Fourier Engle-Granger cointegration test extends the classic two-step Engle-Granger procedure by embedding low-frequency trigonometric (Fourier) terms in the cointegrating regression. This accommodates an unknown number of smooth struct...
Fourier Fixed Effects Model
The Fourier fixed effects model extends standard panel fixed effects regression by augmenting the specification with low-frequency Fourier (trigonometric) terms. These sine and cosine components approximate unknown, smooth structural shifts...