different MLE gives different answers????

1. What is the difference between goodness of fit and maximum
likelihood?

2. If I have understood it correctly in logistic regression one can
use different maximum likelihood equations in order to find the best
fit. So my questions is wouldn’t the answer differ depending on what
maximum likelihood equation one uses?

Best wishes Maria

 

Maximum likelihood is one of the methods that is
used to measure fit, and to compare fits. Sometimes
that is called a "goodness of fit" test. When the comparison
is made to null-hypotheses such as "coefficient equals zero",
the result not usually called a goodness-of-fit test.

Huh? Logistic regression has one standard form.
Different MLE equations .... Would you mean,
for different variables? for different ways of adjusting
for zero-cells, if you are following a discrete solution?

The latter is more common in log-linear modeling, which
is a cousin of logistic regression.

I think you are under some mis-impression about the
existence of "different maximum likelihood equations"
or their nature. Would you want to be more specific,
or have I said enough?

 

Could mean different algorithms for finding the MLE estimates (?). Or
maybe different methods of initializing the algorithm?

Maybe this refers to different link functions?

/Paul

 

Your first question suggests that you study your
material again.

As to the second question, maximum likelihood is maximum
likelihood. For the same model, there is almost always one
absolute maximum, but a computational procedure can
converge to a relative maximum which gives a value below
the absolute maximum.