title: Likelihood ratio test error in R - ANOVA and lrtest
body: <p>I am trying to run a likelihood ratio test in R using lrtest() but it has been giving me errors that I haven't been able to fix:</p>
  
  <pre><code>dat&lt;-read.csv("file.csv", header=TRUE)
  dat1&lt;-glm(Contact~Density + Species, data=dat, family=binomial)
  dat2&lt;-glm(Contact~Density + Species + Mass, data=dat, family = binomial)
  
  lrtest(dat1, dat2)
  Error in UseMethod("logLik") : 
    no applicable method for 'logLik' applied to an object of class "data.frame" 
  
  &gt; dat1
  
  Call:  glm(formula = Contact ~ Density + Species, family = binomial, 
  data = dat)
  
  Coefficients:
  (Intercept)      Density    SpeciesNN  
     -2.0615       0.2522       1.3870  
  
  Degrees of Freedom: 39 Total (i.e. Null);  37 Residual
  Null Deviance:      54.55 
  Residual Deviance: 41.23        AIC: 47.23
  
  &gt; dat2
  
  Call:  glm(formula = Contact ~ Density + Species + Mass, family = binomial, 
  data = dat)
  
  Coefficients:
  (Intercept)      Density    SpeciesNN         Mass  
      -2.5584       0.2524       1.4258       0.2357  
  
  Degrees of Freedom: 39 Total (i.e. Null);  36 Residual
  Null Deviance:      54.55 
  Residual Deviance: 41.11        AIC: 49.11
  </code></pre>
  
  <p><a href="https://www.r-bloggers.com/evaluating-logistic-regression-models/" rel="nofollow noreferrer">According to this link</a>, either ANOVA or lrtest can be used for the likelihood ratio test. I tried the ANOVA method and the test produced results, unlike when I tried using lrtest(). Are both of these interchangeable, or would I miss out on any useful analysis by using ANOVA instead of lrtest?</p>
  
  <p>Edit: Here is a sample of the data set from file.csv.</p>
  
  <pre><code>   Density Species Mass Contact
  1        2      NN 1.29       0
  2        2      NN 2.84       1
  3        2      NN 2.58       0
  4        2      NN 2.81       1
  5        2      NN 2.69       0
  6        2       N 2.12       1
  7        2       N 2.30       1
  8        2       N 1.95       0
  9        2       N 2.35       0
  10       2       N 2.28       1
  11       4      NN 0.90       0
  12       4      NN 2.33       0
  13       4      NN 0.81       1
  14       4      NN 1.37       1
  15       4      NN 1.01       1
  16       4       N 1.94       0
  17       4       N 2.49       0
  18       4       N 2.13       0
  19       4       N 1.90       0
  20       4       N 1.46       0
  </code></pre>