Issue regarding missing values

[shilpa gupta]

Hi
if i run the model without eliminating the missing values, will it effect the output. i am applying random effect logit panel model.

[Carlo Lazzaro]

Shilpa:
but if you delete the missing values, your decision will affect the output too !

[Nick Cox]

In essence Stata will ignore observations with missing values. so you should get the same results, regardless of what you drop or what you exclude with a qualifier.

Other way round, what do you imagine that Stata can or will do here with observations with missing values given your model fit command?

[Hemanshu Kumar]

To back up the point made in #3, if you do help missing, here is what it says under the section "Estimation commands":

Estimation commands

Most Stata commands ignore observations that are missing in one or more of the variables referred to in the command. For instance, the regression command regress disregards all observations that have a missing value for the dependent variable or missing values for any of the independent variables. This method is known as "listwise deletion", "complete cases only", etc. It is statistically appropriate only if the missing values are "at random". In an if or weight expression to a command, the expressions will be evaluated, and the missing values will be processed using the operators and function() logic.

Stata commands that can treat multiple observations as being related to one observational unit (for example, observations from a panel in xt models, episodes in st models) ignore specific observations from the "group", namely, those that have missing values.

[shilpa gupta]

In secondary data, we face the problem of missing values.

Is it advisable to interpolate the data ?

[Carlo Lazzaro]

Shilpa:
if you were the reviewer of your paper, would you consider methpdologically sound to interpolate the data? Would you more in line with reading about missingness mechanism diagnosis and, after that, decide if MI is the way to go?