ltContrast: Calculate linear trend contrast coefficients.
In clayford/dvdata: Data Files for Design and Analysis of Experiments (Dean & Voss)
Description
Usage
Arguments
Examples
Description
Calculates linear trend contrast coefficients according to 4.2.4.
Usage
1
ltContrast(f)
Arguments
f
A factor.
Examples
1
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11
# example 4.23
is.factor(heartlung.pump$RPM) # TRUE
ltc <- ltContrast(heartlung.pump$RPM)
afr <- with(heartlung.pump, tapply(Y,RPM, mean))
# least squares estimate of linear contrast:
crossprod(afr,ltc)
# get msE:
lmHL <- lm(Y ~ RPM, heartlung.pump)
msE <- summary(lmHL)$sigma^2
# estimated standard error of the linear trend estimator:
sqrt(msE * sum(ltc^2/table(heartlung.pump$RPM)))
clayford/dvdata documentation built on May 13, 2019, 7:38 p.m.
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Description Usage Arguments Examples
Description
Calculates linear trend contrast coefficients according to 4.2.4.
Usage
1 | ltContrast(f)
|
Arguments
f |
A factor. |
Examples
1 2 3 4 5 6 7 8 9 10 11 | # example 4.23
is.factor(heartlung.pump$RPM) # TRUE
ltc <- ltContrast(heartlung.pump$RPM)
afr <- with(heartlung.pump, tapply(Y,RPM, mean))
# least squares estimate of linear contrast:
crossprod(afr,ltc)
# get msE:
lmHL <- lm(Y ~ RPM, heartlung.pump)
msE <- summary(lmHL)$sigma^2
# estimated standard error of the linear trend estimator:
sqrt(msE * sum(ltc^2/table(heartlung.pump$RPM)))
|
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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