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# Applied Statistics MCQ

### The opposite process rule says to solve for ________.

Correct Answer: An unknown variable by reversing the process used to form the original equation

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### Moderation involves a situation in which the slope to predict Y from X1 differs across scores on the X2 variable.

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### There are many ways model parameters can be constrained. One type of constraint is created when there is no direct path between two variables is called ____________ .

Correct Answer: Constraints on SEM Model Parameters

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### Kline (2006) recommends that this should also be reported; SRMR > .10 may indicate poor fit. Amos does not provide SRMR is called __________ .

Correct Answer: Standardized Root Mean Square Residual (SRMR)

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### A goodness-of-fit index based on information that compares model fit for the specified model with model fit for the null model the (which represents an assumption that none of the variables are related) is known as:

Correct Answer: Bentler Comparative Fit Index (CFI)

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### Root Mean Square Error of Approximation (RMSEA) model fit index calculates the size of the standardized residual correlations. It ranges from 0 (perfect fit) to 1 (poor fit).

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### One of several indexes of fit that describes how well the overall model paths and coefficients reproduce the variance/covariance information in the data is known as:

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### An analysis that has one or more implied correlations greater than zero in absolute value and/or negative error variance estimates is called ___________ .

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### In binary logistic regression, Model A (e.g., Yi = a + b1 × X1) is nested in Model B (e.g., Yi = a + b1 × X1 + b2 × X2) if all the variables in Model A are also included in Model B, but Model B has one or more additional variables that are not included in Model A.

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### If a structural model has causal loops, it is called _____________ .

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### Models are equivalent when they have identical goodness of fit but include paths that correspond to different hypotheses about which variables are causally related, or direction of causality is known as:

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### Underidentified Model is a model that has more free parameters to estimate than pieces of information in the data; it does not have a unique solution.

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### A model is overidentified if there are more pieces of information in the data (variances and covariances) than free parameter estimates and the model df are positive is known as:

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### A model is just identified if it includes direct paths between all variables and has 0 degrees of freedom is known as:

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### Model Fit is the degree to which the variance/covariance matrix that is reproduced from the paths and coefficients of a structural model matches the variances and covariances estimated using the original data set.

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### Assessment of model identification often involves complex considerations and can be quite difficult (Kenny & Milan, 2012) is called _______________ .

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### Model identification is difficult to assess completely (Kenny & Milan, 2012). One part of this involves comparison of the number of parameters to be estimated versus the number of distinct sample moments is known as:

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### An empirical method for estimation of standard errors and confidence intervals, used in situations where there is no simple formula to calculate these is called ___________ .

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### In structural equation modeling, a model that has no paths among any variables; it represents that assumption that none of the variables are related, causally or non causally is Known as:

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### A model that includes direct paths from each variable to every other variable. It represents the (usually uninteresting) hypothesis that everything is related to everything is called ____________ .

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### For each parameter, the modification index indicates how much overall model fit can be improved by changing that parameter is known as:

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### In a causal model, a unidirectional arrow that points from X toward Y denotes the theoretical existence of a causal connection in which X causes or influences Y (X → Y).

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### In a causal model, a bidirectional arrow is used to represent a situation where two variables are non causally associated with each other; they are

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### A model that represents indicator variables with paths (loadings) that relate them to latent variables (factors) is called _______ .

Correct Answer: Confirmatory Factor Analysis (CFA)

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### A statistic is the best ordinary least squares estimate if it minimizes the sum of squared prediction errors is known as:

Correct Answer: Ordinary Least Squares (OLS)

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### Structural Model is the part of a structural equation model that represents causal (and correlational) paths among latent variables and measured variables.

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### The X variables in a structural equation model that are measured in the study. In an Amos path model, these are represented as a rectangle called _________ .

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