ci.lc.glm: Confidence interval for a linear contrast of general linear...

In statpsych: Statistical Methods for Psychologists

Confidence interval for a linear contrast of general linear model parameters

Description

Computes the estimate, standard error, and confidence interval for a linear contrast of parameters in a general linear model using coef(object) and vcov(object) where "object" is a fitted model object from the lm function.

Usage

ci.lc.glm(alpha, n, b, V, q)

Arguments

alpha	alpha for 1 - alpha confidence
n	sample size
b	vector of parameter estimates from coef(object)
V	covariance matrix of parameter estimates from vcov(object)
q	vector of coefficients

Value

Returns a 1-row matrix. The columns are:

• Estimate - estimate of linear function

• SE - standard error

• t - t test statistic

• df - degrees of freedom

• p - p-value

• LL - lower limit of the confidence interval

• UL - upper limit of the confidence interval

Examples

y <- c(43, 62, 49, 60, 36, 79, 55, 42, 67, 50)
x1 <- c(3, 6, 4, 6, 2, 7, 4, 2, 7, 5)
x2 <- c(4, 6, 3, 7, 1, 9, 3, 3, 8, 4)
out <- lm(y ~ x1 + x2)
b <- coef(out)
V <- vcov(out)
n <- length(y)
q <- c(0, .5, .5)
b
ci.lc.glm(.05, n, b, V, q)

#  Should return:
# (Intercept)          x1          x2 
#   26.891111    3.648889    2.213333 
# > ci.lc.glm(.05, n, b, V, q)
#      Estimate        SE       t df           p       LL       UL
# [1,] 2.931111 0.4462518 6.56829  7 0.000313428 1.875893 3.986329

statpsych documentation built on July 9, 2023, 6:50 p.m.