lmconf<-function(formula, data, ...){
  mformula<-as.formula(formula)
  #create variables predictor and response
  assign( "predictor", data[[as.character(mformula[[3]])]] )
  assign( "response", data[[as.character(mformula[[2]])]] )
  
  lm.can<-lm(response~predictor)
  #lm.can<-lm(data[[as.character(mformula[[2]])]]~data[[as.character(mformula[[3]])]])
  print(anova(lm.can))
  print(summary(lm.can))
  
  new.range<-data.frame("predictor"=seq(min(predictor), max(predictor), length=100))
  fit<-predict(lm.can, newdata=new.range, se.fit=T)
  #plotting
  xmin<-min(predictor, new.range$predictor)
  ymin<-min(response, fit$fit-2*fit$se.fit)
  xmax<-max(predictor, new.range$predictor)
  ymax<-max(response, fit$fit+2*fit$se.fit)  
  plot(response~predictor, xlab=as.character(mformula[[3]]),		    ylab=as.character(mformula[[2]]), xlim=c(xmin,xmax), ylim=c(ymin,ymax))
  lines(new.range$predictor, fit$fit)
  lines(new.range$predictor, fit$fit-2*fit$se.fit, lty=2)
  lines(new.range$predictor, fit$fit+2*fit$se.fit, lty=2)
  
  return(lm.can)
  }