PACKAGE |
|STAT Data Manipulation and Analysis,
by Gary Perlman
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NAME |
regress - multivariate linear regression and correlation
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SYNOPSIS |
regress [-ceprs] [column names]
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WEB FORM |
regress can be run from an
online web form.
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DESCRIPTION |
regress performs a general linear correlation and regression analysis
for up to 20 variables. Input is a series of lines, each containing
an equal number of numerical fields. Names for these fields can be
supplied, but if none are given, REG, A, B, C, etc. are used.
For regression analysis, the first column is predicted with all the
others (see dm or colex to reorder columns).
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OPTIONS |
- -c
- Print the covariance matrix.
- -e
- Save the regression equation in the file regress.eqn. This file
is designed for use with the data manipulator dm. Suppose the
input to regress is in regress.in. Then,
regress -e < regress.in
can be followed by
dm Eregress.eqn < regress.in | pair -p
to plot the obtained against the predicted values. The residuals
can be obtained with an extra pass through dm:
dm Eregress.eqn < regress.in | dm x2 x1-x2 | pair -p
- -p
- Do a partial correlation analysis to determine the contribution
of individual predictors after the others have been included.
regress reports, for each predictor, the regression weight (b)
and the standardized regression weight (beta). The Rsq value is
the squared multiple correlation of the predictor with all other
predictors; if there is only one predictor, this will be zero,
and if there is only one other, both Rsq's will be identical.
Also reported is the standard error of the regression weight (b).
The significance test answers the question: ``After all the other
variables have been taken into account, does this variable
significantly improve prediction?''
- -r
- Do no regression analysis. Only print the correlation matrix and
summary statistics.
- -s
- Print the matrix of raw sums of squares and cross products.
The following standard help options are supported.
The program exits after displaying the help.
- -L
- Display limits
- -O
- Display options and values
- -V
- Display version number and date
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DIAGNOSTICS |
regress will complain about a singular correlation matrix if variables
are perfectly correlated.
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ALGORITHM |
Chapter 4 of Kerlinger and Pedhazur (1973) Multiple Regression in
Behavioral Research. New York: Holt, Rinehart & Winston.
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LIMITS |
Use the -L option to determine the program limits.
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MISSING VALUES |
Cases with missing data values (NA) are counted but not included in
the analysis.
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SEE ALSO |
pair, for simpler paired data analysis.
rankrel, for non-parametric analysis of rank ordinal data.
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UPDATED |
January 27, 1987
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