I have two models, controlled by dummy variables to see if the models can be
combined into one model with similar intercepts and slopes. Has anyone tried
to conduct this type of test in R. I am utilizing the econometric idea of
hypothesis testing through the hypothesis of coincidence. I have tried to
run an anova with test of Chisq, but I am not sure what the results are
telling. In addition, I used the rms package with a lrm model in an anova
test, again I am not sure what the results are telling me:
Try 1
anova(H,Ha,test="Chi")
Analysis of Variance Table
Model 1: logload ~ logflow
Model 2: logload ~ dummy + logflow
Res.Df RSS Df Sum of Sq Pr(>Chi)
1 17 4.6742
2 16 2.6314 1 2.0428 0.0004245 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Try 2:
fit<-lrm(logload~logflow+dummy)
> anova(fit)
Wald Statistics Response: logload
Factor Chi-Square d.f. P
logflow 17.56 1 <.0001
dummy 5.22 1 0.0224
TOTAL 18.03 2 0.0001
Can anyone help me with this?
Thanks!
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