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 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.

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.

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

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 Nov. 19, 2023, 5:12 p.m.