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Multivariate Analysis MCQ

What is the goodness of fit?

How well a model fits the researchers expectations

How well the predictions from a model are consistent with empirical data

The significance level from a statistical test

How well empirical data conform to the technical assumptions of a statistical method

Answer

Correct Answer: How well the predictions from a model are consistent with empirical data

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In the context of SEMs, what is an identified model?

A model which fits the assumptions of the method

A model with enough information to obtain unique estimates of the components of a hypothesised model

A model which confirms the researchers hypotheses

A model which is the simplest possible

Answer

Correct Answer: A model with enough information to obtain unique estimates of the components of a hypothesised model

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Which of the following is NOT required in a structural equation model?

A statement about which relevant variables to include

A hypothesis about causeeffect relationships among variables

Fixed and free parameters

Both latent variables and observed variables

Answer

Correct Answer: Both latent variables and observed variables

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What is the difference between multiple regression analysis and logistic regression analysis?

Logistic regression analysis includes a category dependent variable.

Multiple regression analysis includes more than one dependent variable.

Logistic regression models always contain covariates.

Multiple regression analysis allows predictors to be added sequentially.

Answer

Correct Answer: Logistic regression analysis includes a category dependent variable.

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What is the difference between ANOVA and MANOVA models?

MANOVA models have more than one category predictor variable.

MANOVA models have more than one dependent variable.

MANOVA models always include covariates.

MANOVA models are for multiple groups and ANOVA models are for one group.

Answer

Correct Answer: MANOVA models have more than one dependent variable.

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In hierarchical regression analysis, ______.

The researcher chooses the ordering of predictor variables to be entered based on theory

The order of entering predictor variables depends on the size of their correlations with the dependent variable

The order of entering variables is determined by how well each one adds to predicting the dependent variable

The most important variable is entered first

Answer

Correct Answer: The researcher chooses the ordering of predictor variables to be entered based on theory

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The relative importance of a predictor variable in regression analysis is shown by ______.

A product-moment correlation coefficient

A multiple R coefficient

A regression coefficient

A factor loading

Answer

Correct Answer: A regression coefficient

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Which of the following is NOT required for a multiple regression model?

More than one predictor variable

A category dependent variable

A set of observed variables

A predicted causal model about relationships among variables

Answer

Correct Answer: A category dependent variable

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What is a latent variable?

A variable which cannot be measured directly

A variable whose impact is hidden

A variable which is left out of a causal model

A predictor variable which is not significant

Answer

Correct Answer: A variable which cannot be measured directly

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Which of the following cannot be achieved by using multivariate methods?

Relationships between variables are specific to a single context

Assessing whether relationships between study variables vary depending on the level of other variables

Proving causal relationships between variables

Assessing influences of predictor variables which vary from one dependent variable to another

Answer

Correct Answer: Proving causal relationships between variables

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