What is a Structural Coefficient?

The standardized regression weight (or path coefficient) in the path model.

What is Model Specification?

Defining the variables and the hypothesized paths among them in a model.

What is Model Identification?

Ensuring a model has enough information to estimate all specified parameters.

What is Model Estimation?

The process of calculating values for the model's parameters (e.g., path coefficients).

What is Model Evaluation?

Assessing the fit between the model and the data using various fit indices.

The differences between observed correlations and those reproduced by the model.

What is the Mahalanobis Distance?

A measure used to detect multivariate outliers.

What is the Variance Inflation Factor (VIF)?

A measure of multicollinearity; high VIF indicates high correlation among predictors.

What is Tolerance in the context of VIF?

The inverse of VIF; low tolerance suggests multicollinearity issues.

What is the primary purpose of Path Analysis?

To examine and quantify both direct and indirect relationships among a set of variables based on a hypothesized causal model.

What does Path Analysis clarify?

Causal structure by allowing researchers to test theories about how variables influence each other directly or indirectly.

What does Path Analysis estimate?

Strength of relationships using standardized regression coefficients (path coefficients).

What are Exogenous Variables?

Predictors not influenced by other variables in the model.

What are Endogenous Variables?

Outcomes influenced by other variables in the model.

What is the assumption of Linearity in Path Analysis?

Relationships among variables are assumed to be linear.

What is the assumption of Additivity in Path Analysis?

Effects of independent variables on the dependent variable are additive.

What is the assumption of Causal Direction?

The direction of causal influence must be specified in advance based on theory or prior research.

What is the assumption of Interval-Level Data?

All variables should be measured on at least an interval scale.

What is the assumption of Multivariate Normality?

The variables (especially the residuals) are assumed to follow a multivariate normal distribution.

What is the assumption of No Measurement Error?

Path analysis assumes that all variables are measured without error.

What is the assumption of Independence of Errors?

Error terms are assumed to be uncorrelated with one another and with the variables in the model.

What is the assumption of Sufficient Sample Size?

A large enough sample is required for reliable estimation of path coefficients.

What is a limitation of Path Analysis regarding causality?

Path analysis cannot establish causation-only associations consistent with the model.

What is a limitation of Path Analysis regarding measurement error?

It assumes no measurement error, which may limit its realism.

What is a limitation of Path Analysis regarding model dependence?

Results are only as good as the model specified; poorly specified models yield misleading results.

What is a limitation of Path Analysis regarding multicollinearity?

High correlation between predictors can distort path coefficients.

What is a limitation of Path Analysis regarding observed variables?

Path analysis does not allow for latent variables (i.e., unobserved constructs).

What is Factor Analysis?

A statistical method for identifying underlying variables (factors) that explain the pattern of correlations among observed variables.

What is Confirmatory Factor Analysis (CFA)?

A type of factor analysis used to test whether a hypothesized factor structure fits the observed data.

What is Principal Components Analysis (PCA)?

A data reduction technique that transforms variables into uncorrelated principal components.

What is Exploratory Factor Analysis (EFA)?

Used to explore the possible underlying factor structure of a set of observed variables without a predefined model.

What is Factor Loading?

The correlation between an observed variable and a factor; indicates how well the variable represents the factor.

The proportion of each variable's variance that is explained by the extracted factors.

What is an Eigenvalue?

Represents the amount of variance explained by each factor; factors with eigenvalues >1 are typically retained.

What is a Scree Plot?

A graph of eigenvalues used to determine the number of factors to retain; look for the 'elbow' in the plot.

What is Factor Extraction?

The process of identifying the initial set of factors in the analysis.

What is Factor Rotation?

Adjusts the factor axes to improve interpretability; can be orthogonal or oblique.

What is the Kaiser-Meyer-Olkin (KMO) Measure?

Assesses the adequacy of the sample for factor analysis; values > 0.6 are acceptable.

What is Bartlett's Test of Sphericity?

Tests whether the correlation matrix is significantly different from an identity matrix.

What are Latent Constructs?

Theoretical, unobserved variables inferred from observed variables.

What is the key objective of Factor Analysis?

Data reduction, identifying latent constructs, clarifying variable relationships, improving measurement tools, and enhancing model simplicity.

What is the assumption of Adequate Sample Size in Factor Analysis?

A larger sample size is needed for stable factor solutions, commonly at least 10-15 cases per variable.

What is the assumption of Sufficient Intercorrelations?

There should be a moderate level of correlation among variables; if uncorrelated, factor analysis is inappropriate.

What is a limitation of Factor Analysis regarding subjectivity?

The naming and interpretation of factors can be subjective and influenced by the researcher's judgment.

Path and Factor Analysis Flashcards

Student preview

67 questions

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1.

FLASHCARD QUESTION

Front

What is Path Analysis?

Back

A statistical technique that uses multiple regression to examine hypothesized causal relationships among variables.

2.

FLASHCARD QUESTION

Front

What is a Path Diagram?

Back

A visual representation of hypothesized causal relationships, showing variables and directional paths.

3.

FLASHCARD QUESTION

Front

What is a Direct Effect?

Back

The effect of one variable directly on another, not mediated by any other variables.

4.

FLASHCARD QUESTION

Front

What is an Indirect Effect?

Back

The influence of one variable on another through one or more mediating variables.

5.

FLASHCARD QUESTION

Front

What is a Causal Model?

Back

A theoretical model depicting assumed cause-and-effect relationships among variables.

6.

FLASHCARD QUESTION

Front

What is an Exogenous Variable?

Back

A variable not caused by any other variable in the model; an independent predictor.

7.

FLASHCARD QUESTION

Front

What is an Endogenous Variable?

Back

A variable that is influenced by one or more other variables in the model.

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