Null Model
This article covers meaning & overview of Null Model from statistical perspective.
What is Null Model?
Null Model is a model generated with random samples of a specific distribution where certain elements are constant and others are allowed to vary stochastically. Null model helps in specifying a statistical distribution or randomization of the observed data, designed to predict the outcome of a random process without specifying all of its parameters.
Null model graph is used to match some randomly generated graph, and is believed to be similar until it is proven otherwise. Null Hypothesis is discussed under null model which states that no statistical significance exists in a given set of observations until a statistical evidence nullifies it for an alternate hypothesis. Null models form an intermediary between statistical null hypothesis (one obtained through theories) and Mechanistic models (one obtained through process with all parameters)
Example
Consider a null model with 1 degree of freedom and a log-likelihood of -8024. Similarly assume alternative model with 3 degrees of freedom and a log-likelihood of -8012. Then the probability of its difference is, chi squared value of +2(8024-8012)=24 with 3-1=2 degrees of freedom. Later on by following certain assumptions, chi squared distribution is followed and hence p value is computed.
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