1.
control by adjustment: a form of statistical control in which a mathematical adjustment is made to assess the impact of a third variable
2.
control by grouping: a form of statistical control in which observations identical or similar to the control variable are grouped together
3.
dummy variable: a hypothetical index that has just two values: 0 for the presence (or absence) of a factor and 1 for its absence (or presence)
4.
experimental control: manipulation of the exposure of experimental groups to experimental stimuli to assess the impact of a third variable
5.
explication: the specification of the conditions under which X and Y are and are not related
6.
linear probability model: regression model in which a dichotomous variable is treated as the dependent variable
7.
logistic regression: a nonlinear regression model that relates a set of explanatory variables to a dichotomous dependent variable
8.
logistic regression coefficient: a multiple regression coefficient based on the logistic model
9.
multiple correlation coefficient: a statistic varying between 0 and 1 that indicates the proportion of the total variation in Y, a dependent variable, that is statistically explained by the independent variables
10.
multiple regression analysis: a technique for measuring the mathematical relationships between more than one independent variable and a dependent variable while controlling for all other independent variables in the equation
11.
multiple regression coefficient: a number that tells how much Y will change for a one-unit change in a particular independent variable, if all the other variables in the model have been held constant
12.
multivariate analysis: data analysis techniques designed to test hypotheses involving more than two variables
13.
multivariate cross-tabulation: a procedure by which cross-tabulation is used to control for a third variable
14.
partial regression coefficient: a number that indicates how much a dependent variable would change if an independent variable changed one unit and all other variables in the equation or model were held constant
15.
partly spurious relationship: a relationship between two variables caused partially by a third
16.
regression constant: value of the dependent variable when all the values of the independent variables in the equation equal zero
17.
specified relationship: a relationship between two variables that varies with the values of a third
18.
statistical control: assessing the impact of a third variable by comparing observations across the values of a control variable