linear.hypothesis {car} | R Documentation |
Test a linear hypothesis for a linear or generalized linear model.
linear.hypothesis(model, ...) lht(...) linear.hypothesis.lm(model, hypothesis.matrix, rhs=0, summary.model=summary(model, corr = FALSE), white.adjust=FALSE, error.SS, error.df, ...) linear.hypothesis.glm(model, hypothesis.matrix, rhs=0, summary.model=summary(model, corr = FALSE), ...) ## S3 method for class 'chisq.test': print(x, ...) ## S3 method for class 'F.test': print(x, ...)
model |
model object produced by lm or glm . |
hypothesis.matrix |
matrix (or vector) giving linear combinations of coefficients by rows. |
rhs |
right-hand-side vector for hypothesis, with as many entries as
rows in hypothesis.matrix . |
summary.model |
a summary object for the model; usually specified
only when linear.hypothesis is called from another function that has
already computed the summary. |
white.adjust |
if TRUE use heteroscedasticity-corrected covariance matrix. |
error.SS |
error sum of squares for the hypothesis; if not specified, will be
taken from model . |
error.df |
error degrees of freedom for the hypothesis; if not specified,
will be taken from model . |
x |
chisq.test or F.test object. |
... |
aruments to pass down. |
Computes an F-test for the hypothesis in a linear model, or a Wald test in a generalized linear model.
Returns an F.test
or chisq.test
object, with components:
SSH |
sum of squares for hypothesis (for a linear model). |
SSE |
error sum of squares (for a linear model). |
f |
F-statistic for the hypothesis (for a linear model.) |
Df |
degrees of freedom for F or chisquare. |
p |
p-value for the hypothesis. |
ChiSquare |
chisquare statistic for the hypothesis (for a generalized linear model). |
John Fox jfox@mcmaster.ca
Fox, J. (1997) Applied Regression, Linear Models, and Related Methods. Sage.
data(Davis) mod<-lm(weight~repwt, data=Davis) linear.hypothesis(mod, diag(2), c(0,1)) ## F-Test ## SS = 245.9738 SSE = 12828.03 F = 1.735312 Df = 2 and 181 p = 0.179266