title: R Predict using multiple models
body: <p>I am new to R and trying to predict outcomes on a dataset using 4 different GLM's.  I have tried running as one large model and while I do get results the model doesn't converge properly and I end up with N/A's.  I therefore have four models:</p>
  
  <pre><code>model_team &lt;- glm(mydata$OUT ~ TEAM + OPPONENT, family = "binomial",data =      mydata )
  
  model_conf &lt;- glm(mydata$OUT ~ TCONF + OCONF, family = "binomial",data = mydata)
  
  model_tstats &lt;- glm(mydata$OUT ~ TPace + TORtg + TFTr + T3PAr + TTS. + TTRB. + TAST. + TSTL. + TBLK. + TeFG. + TTOV. + TORB. + TFT.FGA, family = "binomial",data = mydata)
  
  model_ostats&lt;- glm(mydata$OUT ~ OPace + OORtg + OFTr + O3PAr + OTS. + OTRB. + OAST. + OSTL. + OBLK. + OeFG. + OTOV. + OORB. + OFT.FGA, family = "binomial",data = mydata)
  </code></pre>
  
  <p>I then want to predict the outcomes using a different data set using the four models</p>
  
  <pre><code>predict(model_team, model_conf, model_tstats, model_ostats, fix, level = 0.95, type = "probs")
  </code></pre>
  
  <p>Is there a way to use all four models with joining them into one large set?</p>