est: Estimate Linear Functions

In sasLM: 'SAS' Linear Model

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)

Arguments

L	a matrix of linear contrast rows to be tested
X	a model (design) matrix from ModelMatrix
rx	a result of the lfit function
conf.level	confidence level of the 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, the L matrix is for the pairwise comparison such as that of the PDIFF function.

Details

It tests rows of linear functions. A linear function means a linear combination of estimated coefficients. It corresponds to the ESTIMATE statement of SAS PROC GLM. The same sample size per group is assumed for the Tukey adjustment.

Value

Estimate	point estimate of the input linear contrast
Lower CL	lower confidence limit by the "lsd" method
Upper CL	upper confidence limit by the "lsd" method
Std. Error	standard error of the point estimate
t value	value for the t distribution, for methods other than "scheffe"
F value	value for the F distribution, for the "scheffe" method only
Df	degrees of freedom of the residuals
Pr(>|t|)	probability of a larger absolute t value from the t distribution with the residual degrees of freedom, for methods other than "scheffe"
Pr(>F)	probability of a larger F value from the F distribution with the residual degrees of freedom, for the "scheffe" method only

Author(s)

Kyun-Seop Bae [e-mail]

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

sasLM documentation built on June 15, 2026, 9:07 a.m.