REGRESSION ANALYSIS AND REGRESSION LINE
Regression is a measure of association between
two quantitative variables. This form of statistical test is only possible with interval
or ratio data.
If an independent variable and a dependent
variable are placed on the two axis of a graph with the actual data then scattered on the
graph, it is possible to draw a line through the resulting points in a way that minimizes
the distance between the points. The resulting line (which may be straight or curved) is a
Any particular value for the dependent variable
can then be predicted by multiplying the value of independent variable by the regression
coefficient (a number which determines the slope of the line).
In genetics, regression is the tendency of parents
who are exceptional in respect of some partially inherited character to produce offspring
in which this character is closer to the mean value for the general population. Frequently
referred to as regression to the mean.
In psychology, regression is the process of
returning or a tendency to return to an earlier stage of development through hypnosis,
psychoanalysis, mental illness.
On Dummy Variable Regression Analysis -
A Description and Illustration of the Method
Jerry L.L. Miller, Maynard L. Erickson, Department of Sociology, University of
This paper is concerned with the description of a specialized form of linear regression
analysis commonly known as "dummy variable" regression analysis. To show the
relationship between "dummy variable" regression analysis and other multivariate
analysis techniques. (1) to give illustrations and examples of problems to which this type
of multiple-regression analysis might be applied; (2) to show how "dummy
variable" regression analysis is both similar to and different from other
Confronting Sociological Theory with Data:
Regression Analysis, Goodman's Log-Linear Models and Comparative Research -
Bernice A. Pescosolido, Jonathan Kelley
Goodman's log-linear procedure has been advocated as a `better' way of dealing with
certain types of comparisons. There is some question as to their applicability in
answering theoretical questions typically posed in comparative sociological research.
Using a Monte Carlo simulation, we set up a typical but hypothetical set of data that
would be appropriate for testing comparative theories of socioeconomic achievement or
Comparison of Multiple Regression and Configural Analysis Techniques for
Developing Base Expectancy Tables
Dean V. Babst, Don M. Gottfredson, Kelley B. Ballard, JR, Uniform Parole Reports Project,
National Parole Institutes, NCCD, 1966-67
This study compares two statistical techniques, multiple regression and configural
analysis, used in developing parole prediction tables, according to their ability to (1)
differentiate be tween offenders who violate parole and those who do not, (2) predict
violators from among a new group of parolees, and (3) assist administrators and
J. Scott Long and Jeremy Freeses (2003) Regression Models for Categorical
Dependent Variables UsingStata, Revised Edition.