我正在尝试确定泊松或负二项式GLM是分析我的数据的更好模型。这些模型是：
mal_NB <- glm.nb(own_stability ~ own_treatment +
partner_treatment,
data = compiled_mal_2, link = log)
mal_poisson <- glm(own_stability ~ own_treatment +
partner_treatment,
family = poisson(link = "log"), data = compiled_mal_2)
我有两个主要问题，首先，我可以使用似然比检验来比较两者（即R中的lrtest()函数。其次，如何解释该检验的输出（见下文）？
> lrtest(mal_poisson, mal_NB)
Likelihood ratio test
Model 1: own_stability ~ own_treatment + partner_treatment
Model 2: own_stability ~ own_treatment + partner_treatment
#Df LogLik Df Chisq Pr(>Chisq)
1 5 -365.02
2 6 -152.30 1 425.42 < 2.2e-16 ***
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Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1