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.TH subimanova 1 4.6.34 IMOD
.SH NAME
subimanova - subtracts image averages with analysis of variance
.SH SYNOPSIS
subimanova
.SH DESCRIPTION
.P
SUBIMANOVA subtracts one set of average images from another set and
uses a nested analysis of variance (ANOVA) to find the statistical
significance of the difference at each pixel. It then sets to zero
all differences less significant than a specified level. The program
can output either actual differences or pixel values that reflect
the level of significance. In order to do the ANOVA, it must have a
standard deviation or variance image corresponding to each average
image.
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The average and standard deviation/variance images can be ones
produced by IMAVGSTAT or by other means. When one starts the
program, one designates a pair of A files (with average and S.D./VAR
images) and a pair of B files. One can then subtract any set of
sections in B from any set of sections in A; A and B may be the same
pair of files.
.P
The user is responsible for keeping track of how many samples were
used in making each average, and informing this program of those
numbers. The program needs these numbers to do the ANOVA.
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Entries to the program:
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Average image file A
Standard deviation or variance image file A
Average image file B, or Return if same as file for A
Standard deviation or variance image file B, or Return if same as
file for A
Output image file to store differences in
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.P
0 to use a simple mean when combining the average images of one set,
or 1 to form a weighted mean, where each average image would be
weighted by the number of samples combined to form that average.
In the latter case, the mean would be identical to the average
image that could be obtain by combining ALL of the samples of
that set.
.P
0 if the files have standard deviations in them, or 1 if the files
have variances
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Number of differences to compute
.P
For each difference, enter:
.P
List of section numbers in file A, where ranges are allowed
(e.g. 0-2,4,7-8).
.P
List of section numbers in file B, where ranges are allowed
.P
Number of samples making up those averages for each section in A
.P
Number of samples making up those averages for each section in B
.P
Significance level (e.g. 0.05, 0.01, etc). Differences with less
than this significance will be set to zero. Enter a
negative value to have significant pixels values set to
the negative of the log of the probability, or to the positive
log for negative differences. For example, positive and
negative differences with a P of 0.01 would be output as
2 and -2, respectively.
.P
.P
The infamous Satterthwaite approximation will be used whenever the
criteria for its application are satisfied.
.SH HISTORY
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Written by David Mastronarde, 4/23/90
4/12/95 changed to use local subroutines instead of NAG ones
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.SH BUGS
Email bug reports to mast@colorado.edu.