- Computational statistics
- >
- Data mining
- >
- Dimension reduction
- >
- Factor analysis

- Dimensional analysis
- >
- Dimension
- >
- Dimension reduction
- >
- Factor analysis

- Geometric measurement
- >
- Dimension
- >
- Dimension reduction
- >
- Factor analysis

- Mathematical modeling
- >
- Statistical models
- >
- Latent variable models
- >
- Factor analysis

- Statistical analysis
- >
- Multivariate statistics
- >
- Dimension reduction
- >
- Factor analysis

- Statistical theory
- >
- Statistical models
- >
- Latent variable models
- >
- Factor analysis

- Variables (mathematics)
- >
- Hidden variables
- >
- Latent variable models
- >
- Factor analysis

Repertory grid

The repertory grid is an interviewing technique which uses nonparametric factor analysis to determine an idiographic measure of personality. It was devised by George Kelly in around 1955 and is based

The Vectors of Mind

The Vectors of Mind is a book published by American psychologist Louis Leon Thurstone in 1935 that summarized Thurstone's methodology for multiple factor analysis.

Biplot

Biplots are a type of exploratory graph used in statistics, a generalization of the simple two-variable scatterplot.A biplot overlays a score plot with a loading plot.A biplot allows information on bo

Human Cognitive Abilities

Human Cognitive Abilities: A Survey of Factor-Analytic Studies is a 1993 book by psychologist John B. Carroll. It provides an overview of psychometric research using factor analysis to study human int

Parallel analysis

Parallel analysis, also known as Horn's parallel analysis, is a statistical method used to determine the number of components to keep in a principal component analysis or factors to keep in an explora

Principal component regression

In statistics, principal component regression (PCR) is a regression analysis technique that is based on principal component analysis (PCA). More specifically, PCR is used for estimating the unknown re

Factor analysis

Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved variables called factors. For example, it

Congruence coefficient

In multivariate statistics, the congruence coefficient is an index of the similarity between factors that have been derived in a factor analysis. It was introduced in 1948 by Cyril Burt who referred t

Scree plot

In multivariate statistics, a scree plot is a line plot of the eigenvalues of factors or principal components in an analysis. The scree plot is used to determine the number of factors to retain in an

Principal geodesic analysis

In geometric data analysis and statistical shape analysis, principal geodesic analysis is a generalization of principal component analysis to a non-Euclidean, non-linear setting of manifolds suitable

Factor regression model

Within statistical factor analysis, the factor regression model, or hybrid factor model, is a special multivariate model with the following form: where, is the -th (known) observation. is the -th samp

Cultural consensus theory

Cultural consensus theory is an approach to information pooling (aggregation, data fusion) which supports a framework for the measurement and evaluation of beliefs as cultural; shared to some extent b

Varimax rotation

In statistics, a varimax rotation is used to simplify the expression of a particular sub-space in terms of just a few major items each. The actual coordinate system is unchanged, it is the orthogonal

Q methodology

Q methodology is a research method used in psychology and in social sciences to study people's "subjectivity"—that is, their viewpoint. Q was developed by psychologist William Stephenson. It has been

Factor analysis of mixed data

In statistics, factor analysis of mixed data or factorial analysis of mixed data (FAMD, in the French original: AFDM or Analyse Factorielle de Données Mixtes), is the factorial method devoted to data

Functional principal component analysis

Functional principal component analysis (FPCA) is a statistical method for investigating the dominant modes of variation of functional data. Using this method, a random function is represented in the

Exploratory factor analysis

In multivariate statistics, exploratory factor analysis (EFA) is a statistical method used to uncover the underlying structure of a relatively large set of variables. EFA is a technique within factor

Multiple factor analysis

Multiple factor analysis (MFA) is a factorial method devoted to the study of tables in which a group of individuals is described by a set of variables (quantitative and / or qualitative) structured in

Confirmatory factor analysis

In statistics, confirmatory factor analysis (CFA) is a special form of factor analysis, most commonly used in social research. It is used to test whether measures of a construct are consistent with a

FastICA

FastICA is an efficient and popular algorithm for independent component analysis invented by Aapo Hyvärinen at Helsinki University of Technology. Like most ICA algorithms, FastICA seeks an orthogonal

© 2023 Useful Links.