By default lm summary test slope coefficient equal to zero. My question is very basic. I want to know how to test slope coefficient equal to non-zero value. One approach could be to use confint but this does not provide p-value. I also wonder how to do one-sided test with lm.
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2,10,20, labels=c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group)
summary(lm.D9)
Call:
lm(formula = weight ~ group)
Residuals:
Min 1Q Median 3Q Max
-1.0710 -0.4938 0.0685 0.2462 1.3690
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.0320 0.2202 22.850 9.55e-15 ***
groupTrt -0.3710 0.3114 -1.191 0.249
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.6964 on 18 degrees of freedom
Multiple R-squared: 0.07308, Adjusted R-squared: 0.02158
F-statistic: 1.419 on 1 and 18 DF, p-value: 0.249
confint(lm.D9)
2.5 % 97.5 %
(Intercept) 4.56934 5.4946602
groupTrt -1.02530 0.2833003
Thanks for your time and effort.
Use the linearHypothesis function from car package. For instance, you can check if the coefficient of groupTrt equals -1 using.
linearHypothesis(lm.D9, "groupTrt = -1")
Linear hypothesis test
Hypothesis:
groupTrt = - 1
Model 1: restricted model
Model 2: weight ~ group
Res.Df RSS Df Sum of Sq F Pr(>F)
1 19 10.7075
2 18 8.7292 1 1.9782 4.0791 0.05856 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1