regression analysis

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re·gres·sion a·nal·y·sis

the statistical method of finding the "best" mathematical model to describe one variable as a function of another.

re·gres·sion a·nal·y·sis

(rĕ-greshŭn ă-nali-sis)
The statistical method of finding the "best" mathematic model to describe one variable as a function of another.

regression analysis

(in statistics) a test in which the size of one variable (the dependent variable) is dependent on another (the independent variable). Often the relationship is a linear one, enabling a line of best fit to be drawn on a SCATTER DIAGRAM.

re·gres·sion a·nal·y·sis

(rĕ-greshŭn ă-nali-sis)
The statistical method of finding the "best" mathematic model to describe one variable as a function of another.

analysis

separation into component parts.

cohort analysis
the separation of each of two cohorts into component parts and comparing the results.
current analysis
analysis performed on contemporary data.
discriminant analysis
a form of multivariate analysis in which the objective is to establish a discriminate function. The function (typically a mathematical formula) discriminates between individuals in the population and allocates each of them to a group within the population. The function is established on the basis of a series of measurements or observations made on the individuals.
economic analysis
evaluation of the costs and benefits of a commercial enterprise that takes into account additional returns, returns no longer obtained, additional costs and costs no longer incurred, discounting of gains back to the time when the project began, and opportunity costs relating to potential profitability from alternative use of the investment.
factor analysis
a multivariate technique which analyzes the underlying structure of a set of data. It is useful in explaining observed relationships amongst a large number of variables in terms of simpler relations.
guaranteed analysis
declares the range within which nutrients occur in a manufactured animal food.
multivariate analysis
techniques for the study of simultaneous variation in a number of variables. Includes linear discriminant functions, cluster analysis and factor and principal component analysis.
path analysis
a statistical technique for testing a limited number of causal hypotheses, the causal relationships between variables, by manipulation of one or more of the variables and predicting the outcome.
qualitative analysis
determination of the nature of the constituents of a compound or mixture.
quantitative analysis
determination of the proportionate quantities of the constituents of a compound or mixture.
regression analysis
a general statistical technique that analyzes the relationship between a dependent (criterion) variable and a set of independent (predictor) variables.
systems analysis
analysis of the interaction of a system, e.g. a biological system, often for the purpose of analyzing the differences between systems. See also system.
analysis of variance
a statistical method for comparing variables by partitioning the variance of the observations between the effects of the different variables and comparing it with the underlying random variation.
vector analysis
analysis of a moving force to determine both its magnitude and its direction, e.g. analysis of the scalar electrocardiogram to determine the magnitude and direction of the electromotive force for one complete cycle of the heart.

regression

2. subsidence of clinical signs or of a disease process.
3. in biology, the tendency in successive generations toward the mean.
4. the relationship between pairs of random variables; the mean of one variable and its location is influenced by another variable.

regression analysis
see regression analysis.
regression coefficient
is the factor which determines the slope of a regression line; the greater the coefficient the steeper the line.
curvilinear regression
when the relationship between two variables is not linear.
linear regression
the relationship between two variables is a straight line.
References in periodicals archive ?
Each participant's decision policy regarding subordinates' requests for AWAs was determined by ordinary least squares regression analysis on the decision outcomes scale.
Table 1 presents the composite decision policy obtained by ordinary least squares regression on the decision outcomes scale aggregated across all participants.
Six ordinary least squares models are estimated for each year using the CPS and 12 ordinary least squares regressions are estimated using the NLSY--absence of the number of days off variable in the CPS accounts for the discrepancy.
Table 2 contains the results of ordinary least squares regression analyses for the long-term care and ambulatory populations.
The results of ordinary least squares regression analyses examining postintervention dipyridamole expenditures suggest that in both the long-term care and ambulatory populations, the letter intervention had a statistically significant impact on postintervention dipyridamole expenditures per patient relative to the control group when pharmacists alone received the letter or when physicians and pharmacists both received the letter.
The second example involves matrix inversion and ordinary least squares regression.
Data analysis included frequencies, means, one sample t-tests, ANOVA, and ordinary least squares regression.
Findings in ordinary least squares regressions indicated that occupational portrayals of males are most likely to appear in magazines with a high male audience.
Dynamic ordinary least squares regressions are a statistically efficient method for estimating the long-run response of relative export prices to each of these variables (Box B).
Appended are: (1) State indicators for demographic and financial variables; (2) The impact of state financial strategies on high school graduation rates; and (3) Ordinary least squares regressions.
Table : TABLE III Weighted Ordinary Least Squares Regressions Explaining the Net Private Saving Rate (S/Y) With and Without a Measure of the Perceived Likelihood of World War Within Ten Years

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