sasLM (version 0.10.5)

est: Estimate Linear Functions

Description

Estimates Linear Functions with a given GLM result.

Usage

est(L, X, rx, conf.level=0.95, adj="lsd", paired=FALSE)

Value

Estimate

point estimate of the input linear contrast

Lower CL

lower confidence limit by "lsd" method

Upper CL

upper confidence limit by "lsd" method

Std. Error

standard error of the point estimate

t value

value for t distribution for other than "scheffe" method

F value

value for F distribution for "scheffe" method only

Df

degree of freedom of residuals

Pr(>|t|)

probability of larger than absolute t value from t distribution with residual's degree of freedom, for other than "scheffe" method

Pr(>F)

probability of larger than F value from F distribution with residual's degree of freedom, for "scheffe" method only

Arguments

L

a matrix of linear contrast rows to be tested

X

a model (design) matrix from ModelMatrix

rx

a result of lfit function

conf.level

confidence level of confidence limit

adj

adjustment method for grouping. This supports "tukey", "bon", "scheffe", "duncan", and "dunnett". This only affects grouping, not the confidence interval.

paired

If this is TRUE, L matrix is for the pairwise comparison such as PDIFF function.

Author

Kyun-Seop Bae [e-mail]

Details

It tests rows of linear function. Linear function means linear combination of estimated coefficients. It corresponds to SAS PROC GLM ESTIMATE. Same sample size per group is assumed for the Tukey adjustment.

See Also

ESTM, PDIFF

Examples

  x = ModelMatrix(uptake ~ Type, CO2)
  rx = REG(uptake ~ Type, CO2, summarize=FALSE)
  est(t(c(0, -1, 1)), x$X, rx) # Quebec - Mississippi 
  t.test(uptake ~ Type, CO2) # compare with the above