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Social Sciences185

Environment & Sustainability160

手法統計学1,836 人工知能・機械学習1,661 意思決定科学932 研究方法1,354 測定1,745 因果とエビデンス532 研究実践118

1,411 件の手法 · 統計学クリア

フィルターに一致する実在の手法。

並べ替え人気順 A–Z Z–A 新着順

Cohort-Component Projection

Cohort-Component Projection is the standard demographic method for forecasting future population size and age-sex structure by explicitly tracking births, deaths, and migration for each age-sex cohort across discrete time steps. Systematically formalized in the textbook literature by Preston, Heuveline, and Guillot (20

1件の出典2001

Cointegration Test

The cointegration test examines whether non-stationary time series that each contain a unit root share a stable long-run equilibrium relationship. The single-equation residual approach was introduced by Engle and Granger (1987) and the system-based rank approach by Johansen (1988).

2件の出典1988

spatial analysis

Cokriging

Cokriging extends kriging to use one or more correlated secondary variables to improve prediction of a primary variable. When the variable of interest is sparsely sampled but a related, cheaper-to-measure variable is densely sampled, cokriging borrows strength from the secondary variable through their cross-correlation

2件の出典1963

psychotherapy research

Common Factors Questionnaire

The Common Factors Questionnaire (CFQ) is a structured client-report measure that quantifies the client's perception of therapeutic factors deemed common to effective psychotherapy across all modalities—including alliance, therapist empathy, client agency, goal clarity, and emotional expression. Based on Lambert's cont

2件の出典1992

research design

Comparative Relational Survey

A comparative relational survey is a quantitative, non-experimental design that examines the relationships among variables within a single study while simultaneously comparing those relationship patterns across two or more distinct groups. It extends a standard relational (correlational) survey by adding a comparative

2件の出典1960

Competing Risks Analysis

Competing risks analysis, formalized by Fine and Gray in 1999, is a survival analysis framework for settings where a subject can experience one of several mutually exclusive event types. The key quantity is the cumulative incidence function (CIF), which estimates the probability of a specific event occurring by time t

1件の出典1999

Component GARCH

Component GARCH decomposes conditional variance into transitory (short-term) and permanent (long-term) components with different dynamics, allowing flexibility in capturing volatility behavior at multiple frequencies. Introduced by Engle and Lee (1999), it elegantly models the empirical finding that volatility exhibits

2件の出典1999

Compositional Data Analysis

Compositional Data Analysis (CoDA) is a branch of multivariate statistics designed for data that represent parts of a whole — proportions, percentages, or concentrations that sum to a constant. Introduced by John Aitchison in his landmark 1982 paper, CoDA recognises that standard Euclidean methods fail on the simplex a

1件の出典1982

Computerized Adaptive Testing

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

1件の出典2000

research design

Concurrent Multilevel Mixed Methods

Concurrent multilevel mixed methods design collects quantitative and qualitative data simultaneously at two or more levels of a nested social system — for example, students within classrooms within schools — then integrates findings across those levels to produce a layered, comprehensive understanding of the phenomenon

2件の出典2000

Condition Index

The Condition Index, introduced by Belsley, Kuh, and Welsch (1980), is a scalar measure derived from singular value decomposition of the scaled regressor matrix. It quantifies the degree of near-linear dependence among predictors in ordinary least squares regression, enabling analysts to detect collinearity that inflat

1件の出典1980

spatial analysis

Conditional Geostatistical Simulation

Conditional Geostatistical Simulation — most commonly implemented as Sequential Gaussian Simulation (SGS) — generates multiple stochastic realizations of a spatial random field that are each consistent with observed sample data and with a fitted variogram model. Unlike kriging, which produces a single smoothed estimate

1件の出典1997

Conditional Logit

The Conditional Logit Model, introduced by Daniel McFadden in 1974, is a discrete-choice econometric model designed to explain an individual's selection among a finite set of mutually exclusive alternatives. Unlike multinomial logit, it uses covariates that vary across alternatives — such as price, travel time, or prod

1件の出典1974

Conditional Value-at-Risk

Conditional Value-at-Risk (CVaR), also called Expected Shortfall, is a coherent tail-risk measure that quantifies the conditional expectation of losses beyond the Value-at-Risk threshold. It was introduced for optimization by Rockafellar and Uryasev (2000) and shown to be coherent by Acerbi and Tasche (2002), and it ha

2件の出典2000

research statistics

Confidence Interval

A confidence interval (CI) is a range of values, calculated from sample data, that likely contains the true population parameter. Introduced by Jerzy Neyman in 1937, it provides an interval estimate rather than a single point estimate, incorporating both the observed value and the uncertainty around it. The standard 95

3件の出典1937

Confirmatory factor analysis

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

2件の出典1969

Confirmatory Factor Analysis for Scales

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

3件の出典1969

Conformal Prediction (Time Series)

Conformal prediction is a distribution-free wrapper that turns any point forecaster — ARIMA, a neural network, or a machine-learning model — into valid prediction intervals using only its residuals. The time-series form was popularised by Xu & Xie (2021) and the modern tutorial treatment by Angelopoulos & Bates (2023).

2件の出典2021

Conjugate Prior Analysis

Conjugate prior analysis is a class of Bayesian inference methods in which the prior distribution and the likelihood belong to a matched family — called a conjugate pair — so that the posterior distribution has exactly the same functional form as the prior and can be derived in closed form. Introduced systematically by

3件の出典1961

Conover-Iman Test

The Conover-Iman test is a rank-based post-hoc procedure, introduced by Conover and Iman in 1979, that identifies which pairs of groups differ after a significant Kruskal-Wallis or Friedman test. It builds a t-style statistic on the pooled ranks and is generally more powerful than the comparable Dunn test.

2件の出典1979

Contingent Valuation

Contingent Valuation (CVM), developed by Robert Davis in the 1960s, is a survey-based method for estimating the economic value of non-market environmental goods and services—such as wilderness preservation, air quality, or species protection—by directly asking people their willingness to pay (WTP) for specified improve

3件の出典1963

Contrast Analysis

Planned contrast analysis is a parametric hypothesis-testing method that evaluates specific, theoretically motivated comparisons among group means — comparisons that the researcher specifies before data collection, not in response to observed patterns. Formalized comprehensively by Rosenthal, Rosnow, and Rubin (2000),

1件の出典2000

quantitative finance

Copula CDO Model

The copula CDO model (Li 2000) uses Gaussian copulas to price collateralized debt obligations (CDOs) by modeling joint default probabilities across a portfolio of bonds. The model became the industry standard for CDO pricing but was heavily criticized post-2008 for underestimating tail risk and correlation breakdowns d

2件の出典2000

Copula Models

Copula models are a family of functions that describe the dependence structure between variables separately from their individual (marginal) distributions. The foundation is Sklar's theorem (1959), which shows that any multivariate distribution can be split into its marginals plus a copula; Joe (1997) developed the mod

2件の出典1959

Correlation Power Analysis

Correlation power analysis is a pre-study calculation that determines how many participants are needed — or how much statistical power an existing sample provides — for a Pearson correlation test. Formalised by Jacob Cohen in his landmark 1988 text, it uses the expected correlation coefficient r directly as the effect

1件の出典1988

research statistics

Correlation vs Causation

Correlation measures the strength and direction of association between two variables; causation implies that changes in one variable directly produce changes in another. A strong correlation (e.g., r = 0.9) does not prove causation. Classic examples abound: shoe size and reading ability are correlated in children (conf

3件の出典1965

Correspondence Analysis

Correspondence Analysis (CA) is an exploratory multivariate technique for visualizing the association structure of a two-way contingency table. Developed systematically by Jean-Paul Benzécri in France during the 1960s–1970s and brought to an English-language audience by Michael Greenacre in 1984, CA decomposes the chi-

1件の出典1984

COSY

Correlation Spectroscopy (COSY) is a two-dimensional NMR technique that correlates proton chemical shifts through scalar coupling (J-coupling), revealing which protons are magnetically coupled and hence bonded through multiple bonds. Developed by Aue, Bartholdi, and Ernst in 1976, COSY became one of the most important

2件の出典1976

Cox Regression

Cox proportional hazards regression, introduced by D. R. Cox in 1972, is a semi-parametric model that estimates how one or more covariates affect the hazard — the instantaneous rate of experiencing an event — while leaving the baseline hazard function unspecified. It is the standard multivariable method in survival ana

2件の出典1972

Cramer's V

Cramer's V is a nonparametric effect-size statistic that measures the strength of association between two categorical variables on a scale from 0 to 1. Introduced by the Swedish mathematician Harald Cramér in his 1946 work Mathematical Methods of Statistics, it generalises the phi coefficient to tables of any size, mak

1件の出典1946

actuarial science

Credibility Theory

Credibility Theory is an actuarial framework for estimating the pure premium of an individual risk by blending its own observed loss experience with the collective (portfolio) mean. Introduced by Hans Bühlmann in 1967, the method derives the optimal linear combination—the credibility-weighted premium—that minimises mea

1件の出典1967

Credit Risk Models

Credit risk models estimate the probability that a borrower defaults and the resulting distribution of credit losses. The structural approach was introduced by Robert C. Merton in 1974, treating a firm's equity as a call option on its assets, and was later extended into the KMV distance-to-default framework and the Cre

2件の出典1974

Credit Scoring

Credit scoring is a statistical technique that estimates the probability that a borrower will default on a financial obligation. Using Weight of Evidence (WoE) binning, Information Value (IV) variable selection, and logistic regression, it converts raw applicant data into a single integer score. Formalized by Hand and

1件の出典1997

quantitative finance

Credit Valuation Adjustment

Credit Valuation Adjustment (CVA) is the market price of counterparty credit risk embedded in over-the-counter (OTC) derivatives. CVA measures the loss from counterparty default, accounting for both the probability of default and the exposure at that time. It has become a key component of derivative valuation and risk

2件の出典2000

Crime Linkage Analysis

Crime linkage analysis is a forensic method that determines whether a series of crimes were committed by the same offender based on behavioral and modus operandi (MO) similarities. Developed systematically by Craig Bennell and colleagues in the early 2000s, crime linkage applies statistical and similarity-matching tech

3件の出典2002

Cronbach's Alpha

Cronbach's alpha is a coefficient of internal consistency that quantifies the degree to which a set of items on a scale measures the same underlying construct. Introduced by Lee J. Cronbach in 1951, it remains the most widely reported reliability index in social-science, health, and educational research.

2件の出典1951

Cross-Quantilogram

The cross-quantilogram extends the cross-correlogram concept to quantile pairs of two time series, measuring dependence at different quantile levels. Introduced by Linton and Whang (2012), it captures how shocks at specific quantile levels in one series relate to movements in another, enabling asymmetric dependence ana

2件の出典2012

research design

Cross-sectional relational survey

A cross-sectional relational survey collects data from a representative sample at a single point in time and examines the statistical relationships (correlations, associations, predictions) among two or more variables. It combines the temporal efficiency of cross-sectional design with the relational focus of correlatio

Cross-tabulation analysis

Cross-tabulation analysis (contingency table analysis) is a foundational descriptive and inferential technique for examining the relationship between two or more categorical variables. It arranges observed frequencies into a table of rows and columns, enabling visual inspection of patterns and formal chi-square testing

2件の出典1900

experimental design

Crossover A/B Test

A crossover A/B test is an experimental design in which the same participants or units are exposed to both treatment A and treatment B in sequence, with each serving as their own control. By eliminating between-subject variability, the design achieves higher statistical power than a standard parallel A/B test at the sa

2件の出典1949

Croston's Method

Croston's method, introduced by J. D. Croston in 1972, is a time-series forecasting technique built for intermittent demand series in which periods of zero demand are frequent. Instead of forecasting the raw series, it models the size of demand when it occurs and the interval between demand occurrences as two separate

2件の出典1972

CS-ARDL

CS-ARDL (Cross-Sectional ARDL) applies the ARDL framework to panel data while explicitly accounting for cross-sectional dependence—correlation of shocks and relationships across units (countries, firms, regions). Introduced by Pesaran and colleagues (2016), it extends panel ARDL methods to handle common factors or glob

2件の出典2006

CS-DL

CS-DL (Cross-Sectional Distributed Lag) is a simplified dynamic panel model regressing outcomes on current and lagged explanatory variables without explicit autoregressive terms, while accounting for cross-sectional dependence. Built on Pesaran et al. (2001) and extended by Chudik et al. (2014), it estimates dynamic ef

2件の出典2001

CS-NARDL

CS-NARDL extends the nonlinear autoregressive distributed lag (NARDL) model to panel data, capturing asymmetric long-run and short-run relationships where positive and negative changes in explanatory variables have differential effects. Introduced by Shin et al. (2014) and adapted to panels, it allows studying how cros

2件の出典2014

CUSUM Chart

The cumulative sum (CUSUM) control chart, introduced by E. S. Page in 1954, monitors a process by accumulating the deviations of observations from a target value rather than judging each point in isolation. Because small persistent shifts add up over time, the running sum makes them visible far sooner than a Shewhart c

2件の出典1954

CUSUM Test

The CUSUM (Cumulative Sum) and CUSUMSQ (Cumulative Sum of Squares) tests, introduced by Brown, Durbin, and Evans (1975), assess whether the coefficients of a linear regression model remain constant over time. They are standard tools in econometrics for detecting structural breaks, policy shifts, or regime changes in ti

1件の出典1975

DCC-GARCH

DCC-GARCH is Engle's (2002) multivariate volatility model that lets the correlations between several assets change over time. A separate univariate GARCH model is fitted to each series, and then the dynamic correlation matrix is estimated in a second, separate step.

2件の出典2002

DCC-GARCH model

The DCC-GARCH model, introduced by Engle (2002), extends univariate GARCH to capture time-varying correlations between multiple financial time series. It decomposes the multivariate conditional covariance matrix into individual volatility processes and a dynamic correlation matrix, allowing correlations to fluctuate ov

2件の出典2002

DCC-MIDAS

DCC-MIDAS combines dynamic conditional correlation (DCC) GARCH with mixed-frequency data sampling (MIDAS), enabling estimation of time-varying correlations between variables when observations arrive at different frequencies. Introduced by Engle et al. (2013), it models how correlations evolve with low-frequency macroec

2件の出典2013

quantitative finance

Debit Valuation Adjustment

Debit Valuation Adjustment (DVA) represents the value of your own credit risk to counterparties. DVA measures the gain in derivative value if you default on your obligations—a benefit for your shareholders because creditors receive less than the full derivative value. DVA is controversial but now mandatory under IFRS 1

2件の出典2000

DeepHit

DeepHit is a deep neural network framework for survival analysis with competing risks. Introduced by Lee et al. in 2018, it extends DeepSurv to handle settings where multiple, mutually exclusive events can occur, such as disease-specific mortality versus death from other causes. DeepHit solves the challenge of personal

3件の出典2018

DeepSurv

DeepSurv is a deep neural network approach to survival analysis that learns personalized survival distributions directly from data. Introduced by Katzman et al. in 2018, it extends the Cox proportional hazards model using deep learning to capture complex, nonlinear relationships between covariates and survival outcomes

3件の出典2018

Descriptive Statistics

Descriptive statistics is a set of procedures that numerically and visually summarises the essential characteristics of a dataset: central tendency (mean, median, mode), spread (standard deviation, interquartile range), shape (skewness, kurtosis), and frequency distributions. Systematised for applied data analysis by J

1件の出典1977

research design

Design-based Multilevel Mixed Methods

Design-based multilevel mixed methods combines the iterative, context-sensitive logic of design-based research (DBR) with the analytical power of multilevel data structures and the explanatory depth of mixed methods research. It is used predominantly in educational and organizational research where participants are nes

2件の出典2000

DF-GLS Test

The DF-GLS test, introduced by Elliott, Rothenberg, and Stock (1996), is a modified augmented Dickey-Fuller procedure that applies generalized least squares (GLS) detrending before the standard unit-root regression. By removing deterministic components under a local alternative rather than the null hypothesis, the test

1件の出典1996

Diamond-Mortensen-Pissarides Search-Matching

The Diamond-Mortensen-Pissarides (DMP) model, developed by Peter Diamond, Dale Mortensen, and Christopher Pissarides in the early 1980s, is a fundamental framework for understanding labor market dynamics through the lens of search and matching frictions. It explains how workers and firms meet, form employment relations

3件の出典1982

Diebold-Mariano Test

The Diebold-Mariano (DM) test, introduced by Diebold and Mariano in 1995, is a widely used non-parametric procedure for formally comparing the predictive accuracy of two competing forecasting models. It evaluates whether the difference in forecast errors between two models is statistically significant, without requirin

1件の出典1995

DIF Analysis

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

2件の出典1988

Difference GMM

Difference GMM, introduced by Arellano and Bond (1991), estimates dynamic panel data models by first-differencing the equation to remove fixed effects, then using lagged levels of the endogenous variables as GMM instruments. It is the standard approach when a lagged dependent variable or other endogenous regressors are

2件の出典1991

Dirichlet Process Mixture Model

The Dirichlet Process Mixture Model (DPMM) is a nonparametric Bayesian clustering method introduced through Ferguson's (1973) Dirichlet process prior that places a probability distribution over distributions. Unlike finite mixture models, the DPMM does not require the analyst to specify the number of clusters in advanc

3件の出典1973

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