Chapter 9

Question 1

Process in which participants are divided at the “middlemost” score, with 50% of participants above the median termed the “high group,” and the 50% below the median the “low group.”

Answer 1

median split

Question 2

Used to determine the extent of linear relationship between two variables, that is, the extent that variation in one measure is accompanied consistently by unidirectional variation in the other.

Answer 2

Pearson product-moment correlation

Question 3

Squared value of the Pearson correlation, represents the proportion of variance shared between two variables.

Answer 3

coefficient of determination

Question 4

Best fitting straight line drawn through a set of points in a scatterplot

Answer 4

regression line

Question 5

An extension of the Pearson correlation, used to estimated the relationships of multiple predictors to a criterion

Answer 5

multiple regression

Question 6

Also known as standardized weights or beta, are regression weights that have been standardized.

Answer 6

partial correlations

Question 7

Used to estimate the relationship of predictor(s) to a criterion, if the design involves a nested hierarchy of units.

Answer 7

multi-level modeling

Question 8

An index to assess the extent to which participants have more homogenous scores within the higher-order grouping units relative to variability of participant scores across all groupings in a multi-level model.

Answer 8

intraclass correlation

Question 9

Overcomes the limitations of a multiple regression analysis by allowing the ability to estimate relationships among multiple predictors and multiple criterion variables.

Answer 9

structural equation model

Question 10

Type of structural equation model in which predictive relationships involving only measured variables are estimated.

Answer 10

path model

Question 11

A variable not explained by a determinant or predictor (no one-headed arrow is pointing at it)

Answer 11

exogenous variable

Question 12

A variable explained by a determinant or predictor (a one-headed arrow is pointing at it)

Answer 12

endogenous variable

Question 13

Circular processes are not involved, and are therefore amenable to relatively straightforward statistical analysis.

Answer 13

recursive model

Question 14

Allows for causal paths to “backtrack”-in that a variable can be both a cause and an effect of another.

Answer 14

nonrecursive model

Question 15

An integration of confirmatory factor analysis and path analysis.

Answer 15

latent structural equation model

Question 16

An overall index of how well all the computed estimates of the relationships in the model successfully reproduce the underlying correlation matrix.

Answer 16

goodness of fit